Python Developer Jobs in UAE

Job Description<br><br>Job Title: Mathematics Quality Assurance Lead<br><br>Job Type: Contract<br><br>Location: Remote<br><br>About This Role<br><br>In this hourly, remote contractor role, you will work as a Mathematics Quality Assurance Lead to oversee quality, consistency, and trainer performance across mathematics AI training projects. You will review AI-generated math content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for mathematical accuracy, logical reasoning, calculation correctness, proof validity, notation quality, clarity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong mathematics expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote technical teams. This role is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. Your mathematics quality leadership will directly help improve the world’s premier AI models by ensuring that math training data is accurate, logically sound, clearly explained, well-documented, and aligned with client expectations. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.<br><br>Your profile<br><br>Bachelor’s, Master’s, or PhD degree in Mathematics, Applied Mathematics, Statistics, Physics, Engineering, Computer Science, Mathematics Education, or a closely related quantitative field. Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear mathematical feedback in English.3+ years of professional experience in mathematics, teaching, tutoring, research, quantitative analysis, technical writing, curriculum development, problem creation, assessment design, or math-content review. Strong understanding of core mathematics topics such as algebra, geometry, trigonometry, calculus, linear algebra, discrete mathematics, probability, statistics, number theory, combinatorics, differential equations, and mathematical proofs. Ability to evaluate math content against detailed rubrics and identify issues such as incorrect assumptions, flawed reasoning, invalid proofs, calculation errors, notation problems, missing steps, hallucinated facts, or incomplete explanations. Comfortable reviewing both conceptual explanations and step-by-step solutions, including whether each step logically follows from the previous one. Familiarity with mathematical tools or workflows such as LaTeX, Python, MATLAB, R, Wolfram Alpha/Mathematica, Geo Gebra, Desmos, spreadsheet modeling, or symbolic computation tools is preferred. Experience leading or supporting remote teams of trainers, annotators, reviewers, educators, technical writers, or QAs is strongly preferred. Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems. Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and other quality documentation. Experience with AI training, data annotation, large language models, prompt/response evaluation, mathematical content QA, or rubric-based LLM evaluation is a strong plus.<br><br>Key responsibilities<br><br>Quality monitoring: Spot-check mathematics items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues. Mathematical review: Evaluate AI-generated math explanations, proofs, derivations, calculations, word-problem solutions, diagrams/descriptions, and step-by-step reasoning for correctness and clarity. Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and math-specific review standards. Question handling: Respond to trainer/QA questions clearly and promptly, especially around reasoning validity, notation, assumptions, solution methods, proof structure, formatting, and rubric interpretation. Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed. Documentation: Create and maintain mathematics project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials. Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and mathematics-specific review requirements. Quality alignment: Ensure all trainers and QAs apply mathematics guidelines consistently and understand updates as projects evolve. Error-pattern analysis: Identify recurring issues such as skipped reasoning steps, invalid simplifications, wrong formulas, notation inconsistencies, arithmetic mistakes, or answers that are correct but poorly justified. Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for mathematics AI training projects.

Job Description<br><br>Job Title: Astronomer Quality Assurance Lead<br><br>Job Type: Contract<br><br>Location: Remote<br><br>About This Role<br><br>In this hourly, remote contractor role, you will work as an Astronomer Quality Assurance Lead to oversee quality, consistency, and trainer performance across astronomy and astrophysics AI training projects. You will review AI-generated astronomy/astrophysics content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for scientific accuracy, physical reasoning, mathematical correctness, terminology quality, unit handling, observational context, clarity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong astronomy/astrophysics expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote expert teams. This role is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. Your astronomy/astrophysics quality leadership will directly help improve the world’s premier AI models by ensuring that astronomy and astrophysics training data is accurate, physically sound, clearly explained, well-documented, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.<br><br>Your Profile<br><br>Bachelor’s, Master’s, or PhD degree in Astronomy, Astrophysics, Physics, Space Science, Planetary Science, Cosmology, or a closely related field. Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.3+ years of experience in astronomy/astrophysics research, teaching, science communication, academic review, data analysis, observatory work, or related scientific workflows. Strong understanding of celestial mechanics, stellar evolution, galaxies, cosmology, electromagnetic radiation, observational methods, spectroscopy, planetary systems, black holes, and scientific uncertainty. Ability to evaluate astronomy/astrophysics content against detailed rubrics and identify issues such as incorrect physical assumptions, wrong units, flawed calculations, hallucinated facts, misleading explanations, or oversimplified conclusions. Familiarity with tools or methods such as Python, astronomical datasets, telescope/observatory data, spectroscopy, photometry, simulations, LaTeX, Jupyter notebooks, or scientific visualization is preferred. Experience leading or supporting remote teams of researchers, educators, reviewers, annotators, science writers, or QAs is strongly preferred. Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems. Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation. Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, or rubric-based review is a strong plus.<br><br>Key Responsibilities<br><br>Quality monitoring: Spot-check astronomy/astrophysics items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues. Scientific review: Evaluate AI-generated astronomy/astrophysics explanations, calculations, diagrams, observational interpretations, comparisons, and step-by-step reasoning for accuracy and clarity. Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and astronomy/astrophysics-specific review standards. Question handling: Respond to trainer/QA questions clearly and promptly, especially around physical assumptions, units, astronomical terminology, observational methods, formulas, and rubric interpretation. Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed. Documentation: Create and maintain astronomy/astrophysics project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials. Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and astronomy/astrophysics-specific review requirements. Quality alignment: Ensure all trainers and QAs apply astronomy/astrophysics review guidelines consistently and understand updates as projects evolve. Risk review: Flag misleading, overconfident, physically impossible, numerically incorrect, or poorly sourced astronomy/astrophysics claims. Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for astronomy/astrophysics AI training projects.

Job Description<br><br>Job Title: Astronomer Quality Assurance Lead<br><br>Job Type: Contract<br><br>Location: Remote<br><br>About This Role<br><br>In this hourly, remote contractor role, you will work as an Astronomer Quality Assurance Lead to oversee quality, consistency, and trainer performance across astronomy and astrophysics AI training projects. You will review AI-generated astronomy/astrophysics content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for scientific accuracy, physical reasoning, mathematical correctness, terminology quality, unit handling, observational context, clarity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong astronomy/astrophysics expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote expert teams. This role is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. Your astronomy/astrophysics quality leadership will directly help improve the world’s premier AI models by ensuring that astronomy and astrophysics training data is accurate, physically sound, clearly explained, well-documented, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.<br><br>Your Profile<br><br>Bachelor’s, Master’s, or PhD degree in Astronomy, Astrophysics, Physics, Space Science, Planetary Science, Cosmology, or a closely related field. Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.3+ years of experience in astronomy/astrophysics research, teaching, science communication, academic review, data analysis, observatory work, or related scientific workflows. Strong understanding of celestial mechanics, stellar evolution, galaxies, cosmology, electromagnetic radiation, observational methods, spectroscopy, planetary systems, black holes, and scientific uncertainty. Ability to evaluate astronomy/astrophysics content against detailed rubrics and identify issues such as incorrect physical assumptions, wrong units, flawed calculations, hallucinated facts, misleading explanations, or oversimplified conclusions. Familiarity with tools or methods such as Python, astronomical datasets, telescope/observatory data, spectroscopy, photometry, simulations, LaTeX, Jupyter notebooks, or scientific visualization is preferred. Experience leading or supporting remote teams of researchers, educators, reviewers, annotators, science writers, or QAs is strongly preferred. Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems. Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation. Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, or rubric-based review is a strong plus.<br><br>Key Responsibilities<br><br>Quality monitoring: Spot-check astronomy/astrophysics items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues. Scientific review: Evaluate AI-generated astronomy/astrophysics explanations, calculations, diagrams, observational interpretations, comparisons, and step-by-step reasoning for accuracy and clarity. Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and astronomy/astrophysics-specific review standards. Question handling: Respond to trainer/QA questions clearly and promptly, especially around physical assumptions, units, astronomical terminology, observational methods, formulas, and rubric interpretation. Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed. Documentation: Create and maintain astronomy/astrophysics project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials. Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and astronomy/astrophysics-specific review requirements. Quality alignment: Ensure all trainers and QAs apply astronomy/astrophysics review guidelines consistently and understand updates as projects evolve. Risk review: Flag misleading, overconfident, physically impossible, numerically incorrect, or poorly sourced astronomy/astrophysics claims. Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for astronomy/astrophysics AI training projects.

Job Description<br><br>Job Title: Mathematics Quality Assurance Lead<br><br>Job Type: Contract<br><br>Location: Remote<br><br>About This Role<br><br>In this hourly, remote contractor role, you will work as a Mathematics Quality Assurance Lead to oversee quality, consistency, and trainer performance across mathematics AI training projects. You will review AI-generated math content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for mathematical accuracy, logical reasoning, calculation correctness, proof validity, notation quality, clarity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong mathematics expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote technical teams. This role is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. Your mathematics quality leadership will directly help improve the world’s premier AI models by ensuring that math training data is accurate, logically sound, clearly explained, well-documented, and aligned with client expectations. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.<br><br>Your profile<br><br>Bachelor’s, Master’s, or PhD degree in Mathematics, Applied Mathematics, Statistics, Physics, Engineering, Computer Science, Mathematics Education, or a closely related quantitative field. Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear mathematical feedback in English.3+ years of professional experience in mathematics, teaching, tutoring, research, quantitative analysis, technical writing, curriculum development, problem creation, assessment design, or math-content review. Strong understanding of core mathematics topics such as algebra, geometry, trigonometry, calculus, linear algebra, discrete mathematics, probability, statistics, number theory, combinatorics, differential equations, and mathematical proofs. Ability to evaluate math content against detailed rubrics and identify issues such as incorrect assumptions, flawed reasoning, invalid proofs, calculation errors, notation problems, missing steps, hallucinated facts, or incomplete explanations. Comfortable reviewing both conceptual explanations and step-by-step solutions, including whether each step logically follows from the previous one. Familiarity with mathematical tools or workflows such as LaTeX, Python, MATLAB, R, Wolfram Alpha/Mathematica, Geo Gebra, Desmos, spreadsheet modeling, or symbolic computation tools is preferred. Experience leading or supporting remote teams of trainers, annotators, reviewers, educators, technical writers, or QAs is strongly preferred. Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems. Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and other quality documentation. Experience with AI training, data annotation, large language models, prompt/response evaluation, mathematical content QA, or rubric-based LLM evaluation is a strong plus.<br><br>Key responsibilities<br><br>Quality monitoring: Spot-check mathematics items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues. Mathematical review: Evaluate AI-generated math explanations, proofs, derivations, calculations, word-problem solutions, diagrams/descriptions, and step-by-step reasoning for correctness and clarity. Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and math-specific review standards. Question handling: Respond to trainer/QA questions clearly and promptly, especially around reasoning validity, notation, assumptions, solution methods, proof structure, formatting, and rubric interpretation. Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed. Documentation: Create and maintain mathematics project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials. Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and mathematics-specific review requirements. Quality alignment: Ensure all trainers and QAs apply mathematics guidelines consistently and understand updates as projects evolve. Error-pattern analysis: Identify recurring issues such as skipped reasoning steps, invalid simplifications, wrong formulas, notation inconsistencies, arithmetic mistakes, or answers that are correct but poorly justified. Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for mathematics AI training projects.

Department: Internal Audit<br><br>Employment Type: Full Time<br><br>Location: UAE<br><br>Reporting To: Stefani Garvanova<br><br>Description<br><br>About Tabby<br><br>Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money. Over 15 million users choose Tabby to stay in control of their spending and make the most out of their money.<br><br>The company’s flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 40,000 global brands and small businesses, including Amazon, Noon, IKEA, and SHEIN use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores. Tabby generates over $10 billion in annual transaction volume for its partner brands and is the highest-rated, most-reviewed, largest, and fastest-growing Fin Tech in the GCC region.<br><br>Tabby launched in 2019 and has since raised +$1 billion in equity and debt funding from global and regional investors, and is now valued at $4.5 billion.<br><br>About the role:<br><br>We are seeking a dynamic and experienced Internal Audit Senior Manager to lead and develop our Internal Audit function in alignment with regulatory expectations from the Central Bank of the United Arab Emirates and the Institute of Internal Auditors (IIA) Standards.<br><br>This role reports directly to the CEO and the local Audit Committee and offers an exciting opportunity to shape and enhance the internal audit strategy within a fast-growing fintech environment.<br><br>The successful candidate will bring strong fintech industry experience and a forward-thinking approach to designing innovative audit solutions. They will play a critical role in strengthening governance, enhancing regulatory compliance and providing independent assurance across Tabby operations.<br><br>Key Responsibilities<br><br>Establish and lead the Internal Audit function, including building the audit team, operating model, methodology and audit infrastructure in alignment with Institute of Internal Auditors (IIA) Standards and regulatory expectations from the Central Bank of the United Arab Emirates. Conduct enterprise wide risk assessments on a semi-annual basis, to design and maintain a dynamic, risk-based Internal Audit Plan for approval by the Audit Committee. Lead and oversee internal audit engagements across operational, financial, technology, data, product and compliance domains, ensuring high-quality, timely and value-adding audit delivery. Manage co-sourced and outsourced audit providers, to ensure delivery in alignment with internal audit methodology and the necessary level of specialist expertise. Provide clear and insightful reporting to the Audit Committee and senior management, including audit outcomes, key risk exposures, control weaknesses and thematic insights. Oversee issue management and remediation, maintaining a comprehensive audit issues log, tracking corrective actions and validating the effective closure of audit findings. Develop strong and independent relationships with senior stakeholders, providing constructive challenge, risk insights and practical recommendations to strengthen the control environment. Embed data analytics within audit planning and execution, leveraging data-driven techniques to enhance assurance coverage, identify trends and improve audit effectiveness. Promote a strong culture of governance, integrity and continuous improvement.<br><br><br>Skills, Knowledge and Expertise<br><br>Bachelor’s degree in Accounting, Finance, Economics, or a related discipline; a Master’s degree or advanced qualification is preferred. Minimum of 8 years relevant experience in internal audit, risk management or operational control within financial services, fintech or professional services. Strong understanding of internal control frameworks, technology risks, data governance and digital financial products, including Buy Now Pay Later (BNPL) operating models. Familiarity with regulatory expectations of the Central Bank of the United Arab Emirates, including internal control, risk management and governance standards. Proficiency in data analytics and visualization tools (e.g. SQL, Power BI, Tableau or Python), to support audit analytics, control testing and insights-driven reporting. Relevant professional certifications such as Certified Internal Auditor (CIA), Certification in Risk Management Assurance (CRMA), Certified Information Systems Auditor (CISA), or Certified Fraud Examiner (CFE) are advantageous. Strong analytical and critical thinking skills, with the ability to propose innovative solutions and improvements to the control environment. Excellent communication and stakeholder management skills, with the ability to present complex audit findings clearly to stakeholders. Ability to operate effectively in fast-paced, high-growth environments, with a strong focus on execution and delivery. Fluency in English is required; additional languages are considered a plus.<br><br><br>Benefits<br><br>Flexible working model with trust and autonomy from day one. A high-growth environment with ownership and responsibility that will accelerate your career. Participation in the company’s employee stock options program. Comprehensive health insurance. Flexi Perks: a monetary benefit to spend on what matters most to your health, well-being, education, or professional development.

Department: Internal Audit<br><br>Employment Type: Full Time<br><br>Location: UAE<br><br>Reporting To: Stefani Garvanova<br><br>Description<br><br>About Tabby<br><br>Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money. Over 15 million users choose Tabby to stay in control of their spending and make the most out of their money.<br><br>The company’s flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 40,000 global brands and small businesses, including Amazon, Noon, IKEA, and SHEIN use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores. Tabby generates over $10 billion in annual transaction volume for its partner brands and is the highest-rated, most-reviewed, largest, and fastest-growing Fin Tech in the GCC region.<br><br>Tabby launched in 2019 and has since raised +$1 billion in equity and debt funding from global and regional investors, and is now valued at $4.5 billion.<br><br>About the role:<br><br>We are seeking a dynamic and experienced Internal Audit Senior Manager to lead and develop our Internal Audit function in alignment with regulatory expectations from the Central Bank of the United Arab Emirates and the Institute of Internal Auditors (IIA) Standards.<br><br>This role reports directly to the CEO and the local Audit Committee and offers an exciting opportunity to shape and enhance the internal audit strategy within a fast-growing fintech environment.<br><br>The successful candidate will bring strong fintech industry experience and a forward-thinking approach to designing innovative audit solutions. They will play a critical role in strengthening governance, enhancing regulatory compliance and providing independent assurance across Tabby operations.<br><br>Key Responsibilities<br><br>Establish and lead the Internal Audit function, including building the audit team, operating model, methodology and audit infrastructure in alignment with Institute of Internal Auditors (IIA) Standards and regulatory expectations from the Central Bank of the United Arab Emirates. Conduct enterprise wide risk assessments on a semi-annual basis, to design and maintain a dynamic, risk-based Internal Audit Plan for approval by the Audit Committee. Lead and oversee internal audit engagements across operational, financial, technology, data, product and compliance domains, ensuring high-quality, timely and value-adding audit delivery. Manage co-sourced and outsourced audit providers, to ensure delivery in alignment with internal audit methodology and the necessary level of specialist expertise. Provide clear and insightful reporting to the Audit Committee and senior management, including audit outcomes, key risk exposures, control weaknesses and thematic insights. Oversee issue management and remediation, maintaining a comprehensive audit issues log, tracking corrective actions and validating the effective closure of audit findings. Develop strong and independent relationships with senior stakeholders, providing constructive challenge, risk insights and practical recommendations to strengthen the control environment. Embed data analytics within audit planning and execution, leveraging data-driven techniques to enhance assurance coverage, identify trends and improve audit effectiveness. Promote a strong culture of governance, integrity and continuous improvement.<br><br><br>Skills, Knowledge and Expertise<br><br>Bachelor’s degree in Accounting, Finance, Economics, or a related discipline; a Master’s degree or advanced qualification is preferred. Minimum of 8 years relevant experience in internal audit, risk management or operational control within financial services, fintech or professional services. Strong understanding of internal control frameworks, technology risks, data governance and digital financial products, including Buy Now Pay Later (BNPL) operating models. Familiarity with regulatory expectations of the Central Bank of the United Arab Emirates, including internal control, risk management and governance standards. Proficiency in data analytics and visualization tools (e.g. SQL, Power BI, Tableau or Python), to support audit analytics, control testing and insights-driven reporting. Relevant professional certifications such as Certified Internal Auditor (CIA), Certification in Risk Management Assurance (CRMA), Certified Information Systems Auditor (CISA), or Certified Fraud Examiner (CFE) are advantageous. Strong analytical and critical thinking skills, with the ability to propose innovative solutions and improvements to the control environment. Excellent communication and stakeholder management skills, with the ability to present complex audit findings clearly to stakeholders. Ability to operate effectively in fast-paced, high-growth environments, with a strong focus on execution and delivery. Fluency in English is required; additional languages are considered a plus.<br><br><br>Benefits<br><br>Flexible working model with trust and autonomy from day one. A high-growth environment with ownership and responsibility that will accelerate your career. Participation in the company’s employee stock options program. Comprehensive health insurance. Flexi Perks: a monetary benefit to spend on what matters most to your health, well-being, education, or professional development.

Role Summary The Junior Internal Control & Compliance Analyst will support the implementation, monitoring and continuous improvement of internal control, market compliance, anti-corruption, sanctions and KYC processes within a fast-paced energy trading environment. The role requires strong analytical capability, attention to detail, sound judgment and the ability to work closely with front office, operations and support functions to promote a robust culture of compliance.<br>Key Responsibilities<br>Internal Control Administer and maintain the internal procedures database, including drafting, updating, reviewing and ensuring consistency with internal control and governance standards. Manage user administration, including access provisioning and removal, periodic user access and profile reviews, and monitoring to ensure segregation of duties and compliance with internal policies. Coordinate the implementation and follow-up of Return on Experience initiatives, including tracking remediation actions, ensuring timely closure and promoting continuous improvement of internal controls. Monitor and analyse key internal control KPIs, maintain and enhance related reporting tools and escalate relevant findings to management. Support anti-fraud activities, including coordination of investigations, tracking identified risks and incidents, and reporting to relevant governance bodies. Deliver internal control training to new joiners, including onboarding sessions on policies, procedures, systems and key risk areas.<br>Market Compliance Monitor trading activities across relevant markets, including Platts MOC windows and exchanges, using surveillance tools to identify potential market abuse indicators and escalate findings. Review and investigate market conduct alerts using communications monitoring tools, liaise with front office for clarification and document outcomes. Develop, calibrate and improve surveillance scenarios and alerts, ensuring alignment with evolving market risks, trading strategies and applicable regulatory frameworks. Maintain and enhance market compliance dashboards and reporting, including KPI monitoring, trend analysis and preparation of regular reports to management. Provide advisory support to front office on market conduct rules and acceptable behaviours, including MOC participation, information sharing and interactions with brokers and counterparties. Participate in market compliance training and communication initiatives for front office staff, focusing on market abuse risks and real case studies.<br>Anti-Corruption and Economic Sanctions Compliance Perform corruption risk due diligence and analysis on counterparties using dedicated onboarding tools. Conduct sanctions risk analysis and provide advice to front office and operational teams regarding trading and shipping transactions and contracts. Perform sanctions risk analysis and validation for chartering teams through dedicated compliance tools. Conduct regulatory watch and counterparty screening following new sanctions designations. Maintain a database of anti-bribery and economic sanctions-related contractual clauses. Maintain up-to-date compliance documentation and records. Report incidents and compliance breaches in line with internal escalation requirements. Participate in the implementation, maintenance and improvement of dedicated compliance tools. Participate in the review of gifts, hospitality and conflict of interest declarations through dedicated tools. Support training and communication initiatives to monitor effective implementation of compliance policies and contribute to a robust culture of compliance.<br>KYC and Counterparty Onboarding Coordinate with internal teams to provide company and activity information to external counterparties, ensuring successful onboarding and trading readiness. Follow up on onboarding status with counterparties and maintain related registers and dashboards. Manage KYC renewal requests from counterparties. Maintain, update and circulate the BxT KYC information package, coordinating with internal teams for regular updates as required.<br><br>Required Skills and Experience Essential familiarity with Medyssis ETRM, including trading workflows, user access administration, trade data, control points and compliance monitoring requirements. Strong analytical capability, with the ability to review trading, compliance and internal control data, identify trends, investigate exceptions and prepare clear management reporting. Proficiency in Power BI for dashboard development, KPI monitoring, data visualisation and reporting automation. Working knowledge of Python for data extraction, cleansing, analysis and automation of recurring control or compliance monitoring tasks. Good understanding of internal control, market compliance, anti-corruption, sanctions and KYC processes within a commodity or energy trading environment. Excellent written and verbal communication skills, including the ability to document findings, explain control requirements, liaise with front office and operational teams, and escalate issues clearly and professionally. High attention to detail, sound judgment, discretion and ability to manage multiple priorities in a fast-paced trading environment.<br>Candidate Profile The ideal candidate is a proactive, detail-oriented and analytical professional with an interest in internal control, compliance and energy trading. They should be comfortable working with data, systems and cross-functional stakeholders, and able to communicate findings clearly and professionally in a controlled and regulated environment.

Imagine this: Children complete an entire day's worth of academics in two high-intensity hours, then spend their afternoons launching podcasts, creating murals, or mastering gymnastics routines. This is the 2-Hour Learning model that drives Alpha Anywhere—and you are the architect who maintains its momentum while pioneering its next evolution.<br><br>From any location with reliable internet, you'll convert massive volumes of AI-generated performance data into precise, timely interventions that propel each learner toward 90% mastery and beyond. When a learner encounters an obstacle, you'll initiate a live coaching session, eliminate the roadblock in real time, and restore their momentum with renewed confidence. At the same time, you'll analyze rich currents of student performance data, identifying concealed patterns that release children's full capabilities, engineering next-generation AI tools that could double learning velocity.<br><br>Parents observe rising self-assurance, learners double their pace of progress, and you witness the immediate impact of every insight you generate, every AI process you automate, and every question you pose. Prepared to convert data into acceleration fuel for developing minds? Continue reading.<br><br>What You Will Be Doing<br><br>Constructing highly accurate Academic Data Reports and performing systematic analysis to identify issues, detect anomalies, and initiate corrections within 48 hours Facilitating rapid-response intervention sessions and delivering post-assessment coaching calls to eliminate blockers, distinguish knowledge deficits from execution errors, and sustain learner motivation Assessing and deploying new educational applications and content while creating AI/LLM prototypes to advance learning methodologies and address specific challenges Collaborating with leadership to optimize tools, dashboards, and mastery benchmarks as the AI tutor advances<br><br>What You Won’t Be Doing<br><br>Attending endless meetings or delivering generic presentations with no visibility into actual results Grading papers, writing lesson plans, or managing traditional educational programs—the AI and innovation drive our work Working in high-level strategy without implementation or remaining confined to routine tasks—this role is hands-on and dynamic<br><br>Curriculum Developer Key Responsibilities<br><br>Drive improved student learning outcomes through AI-driven analysis and real-time academic insights, demonstrated by enhanced metrics like 2× learning velocity, app engagement, lesson comprehension, response accuracy, and reduced negative learning patterns across the Alpha Anywhere network.<br><br>Basic Requirements<br><br>Demonstrated ability working in data science or related role, education, EdTech, or a student-support role with both analytical and interpersonal components Proficiency in Google Sheets data analysis (lookups, pivot tables, filtering) High emotional intelligence, strong communication skills and a kid-friendly coaching style Experience building workflows and automations with AIAt least 1 year experience working closely with K-8 students Available to work during required core hours of 8:00 AM to 12:00 PM Central Time, Monday through Friday.<br><br>Nice-to-have Requirements<br><br>Background in learning science, educational principles, or demonstrated success improving outcomes through data-driven strategies Experience with Generative AI, prompting techniques, and basic coding skills (Python, Java Script, etc.) for querying AI APIs<br><br>About 2 Hour Learning<br><br>Education is broken, but 2 Hour Learning is proving it doesn’t have to be. They’re tearing down the outdated one-size-fits-all model and replacing it with AI-driven personalized learning that helps kids master academics in just two hours a day.<br><br>With students consistently ranking in the top 1-2% nationally and the top 20% achieving an astonishing 6.5x growth, they’re proving that smarter learning is possible. At 2 Hour Learning, it’s talent and performance that matter. <br><br>They offer a dynamic, on-campus and remote-friendly environment where innovators, educators, and AI specialists can be a part of fixing a broken school system.<br><br>2 Hour Learning is reprogramming learning for the AI era.<br><br>Here’s How They’re Fixing It.<br><br>There is so much to cover for this exciting role, and space here is limited. Hit the Apply button if you found this interesting and want to learn more. We look forward to meeting you!<br><br>Working with us<br><br>This is a full-time (40 hours per week), long-term position. The position is immediately available and requires entering into an independent contractor agreement with Crossover as a Contractor of Record. The compensation level for this role is $30 USD/hour, which equates to $60,000 USD/year assuming 40 hours per week and 50 weeks per year. The payment period is weekly. Consult www.crossover.com/help-and-faqs for more details on this topic.<br><br>Crossover Job Code: LJ-5238-AE-Abu Dhabi-Curriculum Deve1.018

Job Description<br><br>Job Title: Neuroscience Quality Assurance Lead<br><br>Job Type: Contract<br><br>Location: Remote<br><br>About This Role<br><br>In this hourly, remote contractor role, you will work as a Neuroscience Quality Assurance Lead to oversee quality, consistency, and trainer performance across neuroscience and cognitive science AI training projects. You will review AI-generated neuroscience/cognitive science content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for scientific accuracy, conceptual precision, research literacy, experimental-method understanding, brain-behavior reasoning, statistical caution, ethical awareness, clarity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong neuroscience/cognitive science expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote expert teams. This role is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. Your neuroscience/cognitive science quality leadership will directly help improve the world’s premier AI models by ensuring that scientific training data is accurate, evidence-aware, ethically appropriate, clearly explained, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.<br><br>Your Profile<br><br>Bachelor’s, Master’s, PhD, MD/PhD, or equivalent professional background in Neuroscience, Cognitive Science, Psychology, Neurobiology, Cognitive Psychology, Computational Neuroscience, Neurology-adjacent research, Biology, Biomedical Sciences, or a closely related field. Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.3+ years of experience in neuroscience/cognitive science research, teaching, laboratory work, academic review, science communication, experimental design, data analysis, or related scientific workflows. Strong understanding of neural systems, cognition, perception, attention, memory, learning, language, decision-making, neuroanatomy, neural signaling, research methods, and brain-behavior relationships. Ability to evaluate neuroscience/cognitive science content against detailed rubrics and identify issues such as neuromyths, overclaiming, unsupported causal conclusions, flawed study interpretation, incorrect terminology, pseudoscience, or misleading clinical implications. Familiarity with tools or methods such as EEG, f MRI, behavioral experiments, computational modeling, neuropsychological assessment, statistics, Python/R/MATLAB, cognitive tasks, or literature review is preferred. Experience leading or supporting remote teams of researchers, reviewers, educators, annotators, science writers, or QAs is strongly preferred. Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems. Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation. Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, psychology/neuroscience content review, or rubric-based review is a strong plus.<br><br>Key Responsibilities<br><br>Quality monitoring: Spot-check neuroscience/cognitive science items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues. Scientific review: Evaluate AI-generated neuroscience/cognitive science explanations, research summaries, experimental interpretations, brain-behavior claims, cognitive theory applications, and step-by-step reasoning for accuracy and clarity. Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and neuroscience/cognitive-science-specific review standards. Question handling: Respond to trainer/QA questions clearly and promptly, especially around neural mechanisms, cognition, experimental design, statistical interpretation, ethical boundaries, clinical caution, and rubric interpretation. Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed. Documentation: Create and maintain neuroscience/cognitive science project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials. Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and neuroscience/cognitive-science-specific review requirements. Quality alignment: Ensure all trainers and QAs apply neuroscience/cognitive science review guidelines consistently and understand updates as projects evolve. Safety and ethics review: Flag pseudoscientific, overconfident, clinically misleading, ethically problematic, or unsupported claims about the brain, cognition, behavior, or mental health. Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for neuroscience/cognitive science AI training projects.

Job Description<br><br>Job Title: Neuroscience Quality Assurance Lead<br><br>Job Type: Contract<br><br>Location: Remote<br><br>About This Role<br><br>In this hourly, remote contractor role, you will work as a Neuroscience Quality Assurance Lead to oversee quality, consistency, and trainer performance across neuroscience and cognitive science AI training projects. You will review AI-generated neuroscience/cognitive science content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for scientific accuracy, conceptual precision, research literacy, experimental-method understanding, brain-behavior reasoning, statistical caution, ethical awareness, clarity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong neuroscience/cognitive science expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote expert teams. This role is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. Your neuroscience/cognitive science quality leadership will directly help improve the world’s premier AI models by ensuring that scientific training data is accurate, evidence-aware, ethically appropriate, clearly explained, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.<br><br>Your Profile<br><br>Bachelor’s, Master’s, PhD, MD/PhD, or equivalent professional background in Neuroscience, Cognitive Science, Psychology, Neurobiology, Cognitive Psychology, Computational Neuroscience, Neurology-adjacent research, Biology, Biomedical Sciences, or a closely related field. Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.3+ years of experience in neuroscience/cognitive science research, teaching, laboratory work, academic review, science communication, experimental design, data analysis, or related scientific workflows. Strong understanding of neural systems, cognition, perception, attention, memory, learning, language, decision-making, neuroanatomy, neural signaling, research methods, and brain-behavior relationships. Ability to evaluate neuroscience/cognitive science content against detailed rubrics and identify issues such as neuromyths, overclaiming, unsupported causal conclusions, flawed study interpretation, incorrect terminology, pseudoscience, or misleading clinical implications. Familiarity with tools or methods such as EEG, f MRI, behavioral experiments, computational modeling, neuropsychological assessment, statistics, Python/R/MATLAB, cognitive tasks, or literature review is preferred. Experience leading or supporting remote teams of researchers, reviewers, educators, annotators, science writers, or QAs is strongly preferred. Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems. Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation. Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, psychology/neuroscience content review, or rubric-based review is a strong plus.<br><br>Key Responsibilities<br><br>Quality monitoring: Spot-check neuroscience/cognitive science items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues. Scientific review: Evaluate AI-generated neuroscience/cognitive science explanations, research summaries, experimental interpretations, brain-behavior claims, cognitive theory applications, and step-by-step reasoning for accuracy and clarity. Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and neuroscience/cognitive-science-specific review standards. Question handling: Respond to trainer/QA questions clearly and promptly, especially around neural mechanisms, cognition, experimental design, statistical interpretation, ethical boundaries, clinical caution, and rubric interpretation. Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed. Documentation: Create and maintain neuroscience/cognitive science project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials. Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and neuroscience/cognitive-science-specific review requirements. Quality alignment: Ensure all trainers and QAs apply neuroscience/cognitive science review guidelines consistently and understand updates as projects evolve. Safety and ethics review: Flag pseudoscientific, overconfident, clinically misleading, ethically problematic, or unsupported claims about the brain, cognition, behavior, or mental health. Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for neuroscience/cognitive science AI training projects.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <b>Job Description</b><br>We are seeking a highly experienced Digital Delivery Manager to lead, govern, and advance Digital Design delivery across our Buildings Design business. <br>This senior role will be responsible for setting and implementing digital delivery strategies, improving multidisciplinary design workflows, and embedding current and emerging technologies across Architecture, Engineering, Project Delivery and Design Management teams. <br>The successful candidate will combine deep technical knowledge of BIM, Revit-based Delivery, Parametric Design, Design Automation, Digital Twins, and Data-Led Workflows with the leadership capability to drive adoption across a consulting engineering environment<br>Key Responsibilities:<br> Lead the digital delivery strategy for Buildings Design projects, ensuring consistent, efficient, and high-quality delivery across multidisciplinary teams.<br> Assist/Input into the production, oversee the implementation, and ensure maintenance of BIM execution plans, digital delivery standards, model production protocols, information management workflows, and quality assurance procedures.<br> Champion ISO 19650-aligned information management, Common Data Environment governance, model federation, clash detection, issue management, data validation, and structured digital handover processes.<br> Provide leadership to the BIM Managers for Revit-based design delivery across architectural, structural, mechanical, electrical, public health, and specialist design disciplines.<br> Drive the adoption of parametric and computational design workflows using tools such as Rhino, Grasshopper, Dynamo, Python, and related scripting or visual programming environments.<br> Identify opportunities to convert analogue or repetitive design, checking, reporting, and coordination processes into automated digital workflows.<br> Lead the implementation of design automation tools that improve productivity, reduce rework, enhance quality, and support more consistent design outcomes.<br> Guide project teams in the development and implementation of Digital Twin strategies, including asset data structuring, model readiness, operational data requirements, and lifecycle information handover.<br> Evaluate and integrate emerging digital delivery technologies, including AI-assisted design workflows, model checking platforms, automated reporting tools, data dashboards, reality capture, cloud collaboration platforms, and Digital Twin environments.<br> Work closely with design directors, project managers, discipline leads, BIM managers, and delivery teams to align digital solutions with business objectives and project requirements.<br> Establish training, mentoring, and upskilling programmes to improve digital capability across design teams.<br> Act as the senior digital delivery point of contact for clients, partners, subconsultants, contractors, and internal leadership teams.<br> Ensure any new protocols align with the wider Stantec Group policies and procedures.<br> Engage with Global initiatives for standardisation of Stantec workflows and standards, representing Buildings Middle East.<br><br><br><b>Qualifications</b><br> Bachelor’s degree in Architecture, Engineering, Construction Management, Computational Design, Digital Design, or a related built environment discipline.<br> Professional certifications in BIM, Digital Delivery, Information Management, or relevant software platforms are highly desirable.<br> Autodesk Certified Professional, Revit certification, Computational Design training, or equivalent technical credentials would be advantageous.<br> Minimum 10–15 years of progressive experience in BIM, digital delivery, design technology, or related roles within an engineering consultancy, architecture practice, multidisciplinary design firm, or major built environment organisation.<br> At least 5 years in a leadership role managing BIM, digital delivery, computational design, automation, or information management teams driving adoption and transformational change at a regional business level.<br> Proven experience delivering complex Buildings Design projects across multiple disciplines and project stages, from concept design through detailed design, tender, construction support, and handover.<br> Demonstrated experience developing and implementing BIM standards, digital delivery frameworks, automation strategies, and project-specific digital execution plans.<br> Strong understanding of engineering consultancy workflows, design coordination requirements, project delivery governance, and client-facing delivery expectations.<br>Technical Knowledge and Software Requirements:<br> Advanced knowledge of BIM authoring and coordination tools, particularly Autodesk Revit, Navisworks, Autodesk Construction Cloud, BIM 360, BIM Collaborate Pro, and related Autodesk ecosystem tools.<br> Strong working knowledge of model federation, clash detection, issue tracking, model auditing, information exchange, and digital QA/QC workflows.<br> Advanced understanding of parametric and computational design platforms such as Rhino, Grasshopper, Dynamo, and associated plug-ins or scripting environments.<br> Knowledge of design automation approaches using Dynamo, Grasshopper, Python, C#, APIs, custom Revit add-ins, Rhino.Inside.Revit, Speckle, Power Automate, Power BI, and other workflow automation platforms.<br> Familiarity with Digital Twin development and implementation, including asset information requirements, data schemas, model classification, IoT integration concepts, operational readiness, and integration with facilities management or asset management systems.<br> Experience with Common Data Environments and collaboration platforms such as Autodesk Construction Cloud, ProjectWise, Trimble Connect, BIMcollab, Revizto, SharePoint, and similar project delivery environments.<br> Awareness of current and emerging tools for reality capture, laser scanning, photogrammetry, AI-assisted model checking, generative design, automated code checking, data dashboards, and model-based reporting.<br> Strong understanding of ISO 19650 principles, BIM Execution Plans, Exchange Information Requirements, Asset Information Requirements, naming conventions, classification systems, and information delivery milestones.<br>Design Automation and Innovation Competencies:<br> Ability to identify repetitive design, documentation, checking, scheduling, quantity extraction, reporting, and coordination tasks that can be automated.<br> Experience developing or leading automation workflows that improve speed, accuracy, consistency, and design quality.<br> Ability to translate analogue processes, spreadsheet-based tools, manual checking routines, and discipline-specific workflows into scalable automated solutions.<br> Strong understanding of data-driven design, computational logic, interoperability, open data exchange, and integration between modelling, analysis, reporting, and project controls systems.<br> Ability to evaluate new technology against business value, project needs, user adoption, risk, cost, and measurable productivity benefits.<br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <b>Overview:</b> <br><p><strong>About Analog</strong></p><br><br><br><p>Analog is pioneering the era of physical intelligence. Where digital intelligence transformed our online lives, Analog is transforming the lived world, making cities more adaptive, industries more resilient, services more human centered, and experiences more extraordinary.</p><br><br><br><p>At the heart of our approach are living world models, continuously updated, enriched by every capture point, every device, every interaction. Within them resides Ana, the Analog Neural Agent. Ana perceives, adapts, and guides, transforming raw data into foresight and orchestration that improves outcomes across sectors, from safeguarding high-value assets to enhancing human performance.</p><br><br><br><p><strong>Job Description</strong></p><br><br><p>We are seeking a highly skilled <strong>Senior Security Engineer</strong> to be the first hire in our Infosec team. This is a hands-on technical leadership role with high growth potential in a cutting-edge AI driven organization. The ideal candidate will have deep expertise in designing, implementing, and maintaining end-to-end security solutions across infrastructure, applications, and data. As the first dedicated security hire, you will play a pivotal role in building and shaping our cybersecurity strategy and practices from the ground up.</p><br><br><br><p>In this role, you will be responsible for planning, designing, and implementing security solutions, identifying risks, and ensuring compliance with industry standards. You will work closely with cross-functional teams to embed security at every level of our technology and business processes. You will also play a lead role in developing a longer term security improvements roadmap, setting the foundation for future team expansion and required security tooling investments. If you are an experienced, hands-on security professional eager to make a significant impact in a high-growth organization, we encourage you to apply.</p><br><br><b>Responsibilities:</b> <br><ul><li><strong>Security Strategy &amp; Roadmap</strong>: Develop a comprehensive security roadmap that aligns with business strategy, supporting product launches and future business growth.</li><li><strong>Security Architecture</strong>: Design, implement, and manage security architectures for cloud, on-premises, and hybrid environments.</li><li><strong>Policies &amp; Standards</strong>: Develop, enforce, and continuously improve security policies, frameworks, and best practices across the organization.</li><li><strong>Risk &amp; Compliance</strong>: Conduct risk assessments, threat modeling, and vulnerability management to proactively mitigate security threats, while ensuring compliance with relevant security standards e.g. ISO 27001, NIST, GDPR, SOC 2, and CIS benchmarks</li><li><strong>Incident Management:</strong> Lead incident response efforts, including investigation, containment, remediation, and post-mortem analysis.</li><li><strong>Security Testing</strong>: Perform penetration testing, security audits, and compliance assessments to validate security posture.</li><li><strong>Security Tooling</strong>: Deploy and manage security solutions such as SIEM, IDS/IPS, endpoint protection, IAM, firewalls, and encryption technologies.</li><li><strong>Collaboration &amp; Communication</strong>: Works closely with Engineering, DevOps, and IT teams to integrate security into system architectures and software development processes (DevSecOps). Communicates security risks and recommendations effectively to technical and non-technical stakeholders.</li><li><strong>AI &amp; Data Security</strong>: Develop &amp; implement security measures to protect AI models, data pipelines and APIs from adversarial attacks and data leakage.</li><li><strong>Emerging Trends</strong>: Stays current with evolving cyber threats, attack techniques, and security trends, applying knowledge to strengthen defenses.</li><li><strong>Training &amp; Awareness:</strong> Develop and conduct security awareness training programs to foster a strong security culture within the organization.</li><li><strong>External Partnerships:</strong> Establish relationships with external security vendors, partners, and regulatory bodies to leverage expertise and support.</li></ul><br><b>Qualifications:</b> <br><ul><li>Bachelor’s or Master’s degree in Computer Science, Information Security, or a related field.</li><li>Minimum of 5 years of hands-on experience in cybersecurity, information security, or a related field.</li><li>Proven experience in security architecture, engineering, and operations in cloud (AWS, Azure, GCP) and on-prem environments.</li><li>Strong knowledge of security frameworks such as NIST, ISO 27001, CIS Controls, and Zero Trust architecture.</li><li>Hands-on experience with security tools, including firewalls, SIEM, EDR, IDS/IPS, vulnerability scanners, DLP, and encryption.</li><li>Expertise in security incident response, threat intelligence, and forensic investigations.</li><li>Experience with identity and access management (IAM), multi-factor authentication (MFA), and privilege access management (PAM).</li><li>Proficiency in programming and scripting languages such as Python, PowerShell, or Bash</li><li>Industry certifications such as CISSP, CISM, CEH, OSCP, or equivalent are highly preferred.</li><li>Strong knowledge of DevSecOps principles and secure software development practices.</li><li>Demonstrated ability to communicate effectively with both technical and non technical audiences.</li><li>Experience working with security governance, risk management, and compliance (GRC) programs.</li><li>Excellent problem-solving, analytical, and communication skills with the ability to work independently and collaboratively.</li></ul><br><p><strong>Good-to-Have Experience</strong></p><br><br><br><ul><li>Experience with physical security measures, such as facility access controls, video surveillance, and security monitoring systems.</li><li>Knowledge of IoT security, industrial control systems (ICS) security, and supply chain security.</li><li>Experience implementing Zero Trust and Secure Access Service Edge (SASE) architectures.</li><li>Understanding of AI security risks and model protection strategies</li><li>Prior experience working in high growth technology start ups.</li></ul><br><p>If you are passionate about cybersecurity and want to build and lead the security function in a high-growth, innovative organization, we would love to hear from you!</p><br><br><br><br><p><strong>What Working At Analog Offers</strong></p><br><br><br><ul><li>Culture: A collaborative, globally minded team building the future of physical intelligence. We value curiosity, courage, and creativity, and we’re united by a belief that technology should amplify human potential rather than replace it.</li><li>Impact: The opportunity to work on projects with national and global significance, from adaptive cities and resilient infrastructure to next generation sports, entertainment, healthcare, and energy. Every product you help build contributes to shaping a safer, smarter, more human centered world.</li><li>Growth: Outstanding opportunities for learning and career development. You’ll collaborate with leaders across AI, robotics, mixed reality, and systems engineering, while working on industry first, frontier scale solutions.</li><li>Rewards: A competitive compensation package with healthcare, education support, and generous leave benefits, reflecting the high value we place on our people and their families.</li></ul><br><br> </div>

<p>The AI Engineer / Agent Developer is the hands-on builder of the Group’s Agentic AI capability, turning approved use cases into working, reliable agents that operate safely against real enterprise systems and data. The role spans rapid prototyping and production engineering — designing prompts and retrieval strategies, integrating agents with core platforms and tools, and instrumenting them so that accuracy, reliability, cost, and exception handling can be measured and improved. Success is judged not by demonstrations but by agents that hold up in daily business use under enterprise standards of security and control. </p><p><strong>▶ Agent Development & Engineering</strong> – Build, configure, and test AI agents against defined business use cases, translating solution blueprints into working implementations. – Work hands-on across prompt engineering, retrieval-augmented generation (RAG), workflow automation, API development, and tool integration. – Implement agent reasoning patterns, tool selection logic, memory and context management, and structured output handling. – Design and implement guardrails — input validation, output constraints, confidence thresholds, and safe failure behaviour. – Apply disciplined engineering practice: version control, code review, environment separation, automated testing, and CI/CD pipelines. ▶ <strong>Prototyping & Production Deployment</strong> – Develop rapid prototypes that prove or disprove feasibility quickly, with clear articulation of assumptions and limitations. – Support the transition of validated prototypes into production deployment, including hardening, performance tuning, and operational documentation. – Prepare release artefacts, runbooks, and support handover materials for infrastructure and application support teams. – Contribute to shared libraries, reusable components, prompt templates, and evaluation harnesses that accelerate future builds. ▶ <strong>Enterprise Systems Integration</strong> – Connect AI agents with enterprise systems, documents, databases, and workflow tools, including ERP, CRM, HRMS, procurement, and document repositories. – Build and consume secure APIs and integration services, managing authentication, rate limits, error handling, and retry logic. – Implement human-in-the-loop approval steps and escalation routes so that agent actions remain reviewable and reversible. – Coordinate with enterprise application owners on data contracts, sandbox access, regression testing, and release windows. ▶ <strong>Performance Monitoring & Quality Assurance</strong> – Monitor agent performance, accuracy, reliability, latency, and exception handling in both test and production environments. – Build evaluation datasets and automated test suites to detect regression when prompts, models, or upstream data change. – Investigate failures and unexpected behaviour to root cause, and implement corrective changes with documented evidence of improvement. – Track token consumption and inference cost, and optimise model selection, context size, and caching accordingly. ▶ <strong>Collaboration, Security & Documentation</strong> – Work closely with the AI / Agentic AI Lead, data engineers, application specialists, and business users throughout the delivery cycle. – Apply cybersecurity and data protection requirements in every build, including data classification, secrets management, and least-privilege access. – Maintain clear technical documentation covering architecture, prompts, integrations, known limitations, and support procedures. – Support user enablement by demonstrating capability, gathering structured feedback, and iterating on real-world usage. </p><p><strong>Desired Candidate Profile</strong></p><p>▶ Education – Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, Information Technology, or a related discipline. – Postgraduate qualification in Artificial Intelligence, Machine Learning, or Data Science is an advantage. ▶ Professional Certifications – Certification in a major AI or cloud platform (Microsoft Azure AI Engineer, AWS Machine Learning, Google Cloud Professional ML Engineer, or equivalent). – Developer-level certifications in Python, cloud application development, or integration platforms are advantageous. – Recognised training in Agentic AI frameworks, RAG architecture, or LLM application security is an asset. ▶ Experience – 4–7 years of experience in software development, automation, data engineering, AI/ML, or enterprise application integration. – Hands-on experience in building, configuring, testing, and deploying AI agents or GenAI-based applications. – Experience with AI/GenAI platforms such as OpenAI API, Microsoft Copilot Studio, Amazon Bedrock, Google Vertex AI, or similar. – Familiarity with Agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar. – Demonstrated experience integrating applications with enterprise systems, databases, document repositories, and workflow tools. – Exposure to production support, monitoring, and incident resolution for deployed solutions. ▶ Key Skills & Attributes – Strong practical coding ability, with clean, testable, and well-documented implementation. – Structured debugging and root-cause analysis for probabilistic systems where failures are not always reproducible. – Clear judgement on when a prototype is genuinely production-ready and when it is not. – Ability to work directly with business users to refine requirements and validate outputs. – Disciplined approach to security, data protection, and access control in every build. – Curiosity and self-directed learning in a technology area that changes month to month </p>

<ul><li><p>We are looking for an experienced AI Architect responsible for architecting enterprise-wide Generative AI and Agentic AI capabilities across banking systems. The role will define target architecture, integration patterns, standards, reference implementations and reusable building blocks for full-fledged AI chat assistants, autonomous agents and multi-agent workflows. The AI Architect will lead end-to-end architecture for agentic retail banking journeys such as payments, transfers, servicing, self-service fulfilment and customer assistance, ensuring secure integration with enterprise APIs, middleware, core banking platforms and customer-facing channels across web and mobile. This role requires deep hands-on AI engineering capability, strong banking domain understanding, practical delivery experience with multiple production-grade banking agents, and the ability to collaborate with product, engineering, infrastructure, cybersecurity, data, governance and enterprise architecture teams to present and align designs through ARB.</p></li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li><p>Minimum Qualification</p><ul><li><p>Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, Data Science or a related discipline.</p></li><li><p>Relevant certifications in cloud architecture, AI engineering, security architecture, enterprise architecture or machine learning are preferred.</p></li></ul><p>Minimum Experience</p><ul><li><p>Senior technology professional with around 12+ years of experience across software engineering, architecture, cloud/platform engineering and enterprise solution delivery.</p></li><li><p>Minimum 4+ years of hands-on AI engineering or AI architecture experience, including Generative AI, LLM applications and Agentic AI solutions.</p></li><li><p>Proven experience architecting and delivering multiple banking agents or full-fledged banking chat assistant capabilities integrated with enterprise systems.</p></li><li><p>Strong understanding of banking systems, retail banking journeys, payments, transfers, servicing, customer self-service, operational controls and regulatory/security considerations.</p></li><li><p>Full AI Engineer capability including Python, API integration, microservices, event-driven design, RAG implementation, model/agent evaluation and cloud-native deployment practices.</p></li><li><p>Hands-on experience with agent frameworks and orchestration platforms such as Microsoft Semantic Kernel, AutoGen, LangChain, LangGraph and similar frameworks.</p></li><li><p>Experience architecting MCP servers, tool integration layers, agent-to-agent communication, UI integration patterns and agent interoperability protocols such as MCP, A2A and A2UI.</p></li><li><p>Strong experience with Azure AI services, Azure OpenAI Service, AWS AI services, Amazon Bedrock and related model deployment/management capabilities.</p></li><li><p>Experience designing secure AI systems with zero trust principles, identity and access controls, data protection, secure API design, PII redaction and privacy-by-design controls.</p></li><li><p>Experience presenting solution architecture, trade-off analysis, ADRs and architecture recommendations to ARB or equivalent architecture governance forums.</p></li><li><p>Experience recommending infrastructure architecture for AI platforms including compute, Kubernetes, serverless, vector databases, observability, monitoring, data pipelines and connectivity.</p></li><li><p>Strong capability to collaborate with engineering, product, cybersecurity, infrastructure, operations, data, compliance and enterprise architecture teams.</p></li></ul></li></ul><br><p>Key Technical Skills</p><ul><li><p>Enterprise Agentic AI architecture, multi-agent systems, autonomous workflows, human-in-the-loop design and full-fledged chat assistant architecture.</p></li><li><p>LLMs, prompt engineering, context engineering, memory design, tool/function calling, agent orchestration, model/agent evaluation and cost/latency optimization.</p></li><li><p>RAG architecture, semantic indexing, embeddings, vector databases, retrieval optimization, reranking, grounding, answer relevancy and explainability patterns.</p></li><li><p>MCP server architecture, tool registries, multi-tool integration, A2A, A2UI, agent interoperability protocols and AI ecosystem design.</p></li><li><p>Azure AI, Azure OpenAI, AWS AI services, Amazon Bedrock, Kubernetes, serverless, microservices, APIs, event-driven architecture and observability.</p></li><li><p>Security architecture for AI systems including zero trust, PII redaction, data masking, privacy controls, guardrails, secure logging and auditability.</p></li></ul><p>Behavioural / Leadership Skills</p><ul><li><p>Strategic architecture thinking with the ability to define enterprise standards, influence platform direction and simplify complex technical decisions.</p></li><li><p>Strong stakeholder communication with the ability to present architecture options, risks, trade-offs and recommendations to senior leadership and ARB forums.</p></li><li><p>Collaborative leadership style with the ability to work across business, product, engineering, cybersecurity, data and infrastructure teams.</p></li><li><p>Hands-on problem-solving mindset, pragmatic decision making, ownership, mentoring capability and commitment to high-quality secure delivery.</p></li></ul><p>Technical Competencies</p><ul><li><p>Enterprise Agentic AI architecture and banking-grade AI ecosystem design.</p></li><li><p>Retail banking agent architecture for payments, transfers, servicing and self-service workflows.</p></li><li><p>RAG, memory, context engineering, evaluation, tool orchestration and MCP server architecture.</p></li><li><p>AI security architecture, zero trust, PII redaction, guardrails, auditability and governance.</p></li><li><p>Azure and AWS AI services, cloud-native infrastructure, Kubernetes, serverless and observability for agent platforms.</p></li><li><p>Architecture documentation, ADR creation, ARB presentation and cross-team design governance.</p></li></ul><p>Skills</p><p>AI Architecture</p><p>LLMs</p><p>Azure AI</p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span><span><span><strong><span>Senior DevOps Engineer</span></strong></span></span></span><br> <span><span><span><strong>Location:&nbsp; </strong><span>Abu Dhabi, UAE</span></span></span></span><br> <span><span><span><strong>Experience:&nbsp; </strong><span>8+ years</span></span></span></span> <span><span><span><strong><span><span>About the Role</span></span></strong></span></span></span> <br> <span><span><span>We are looking for a highly skilled Senior DevOps Engineer to help design, build, and operate large-scale, production-grade Azure environments. You will work across the full delivery chain from CI/CD and infrastructure to observability, security, and cost on a modern, Azure-native, microservices-based platform.</span></span></span><br> <span><span><span>This is a hands-on engineering role for someone who's comfortable owning production systems end to end, automating everything that can be automated, and raising the bar on security, scalability, and cost efficiency across the team. Curiosity about applying AI/ML to platform engineering, &nbsp;multi-agent assistants, MCP-based integrations, Azure AI Foundry is a real plus.</span></span></span> <span><span><span><strong><span><span>What You'll Do</span></span></strong></span></span></span> <br> <ul> <li><span><span><span>Design, build, and maintain end-to-end CI/CD pipelines for complex microservices across Dev / Test / Staging / Prod, including build fan-out, parallel lanes, quality gates, and controlled release/promotion strategies.</span></span></span> </li><li><span><span><span>Own and evolve Azure infrastructure AKS, Azure Front Door, Application Gateway, APIM, ACR, Azure DevOps, and supporting services with a focus on reliability, security, and scalability.</span></span></span> </li><li><span><span><span>Implement Infrastructure as Code and GitOps practices as the source of truth for environments and deployments.</span></span></span> </li><li><span><span><span>Embed security into the delivery lifecycle (DevSecOps): SAST, DAST, SCA, container image scanning, secret scanning, and policy-as-code.</span></span></span> </li><li><span><span><span>Drive observability: instrumentation, dashboards, alerting, distributed tracing, and fast diagnosis of production issues.</span></span></span> </li><li><span><span><span>Champion FinOps and cost-awareness monitor, allocate, and optimize cloud spend, and partner with engineering and finance stakeholders.</span></span></span> </li><li><span><span><span>Contribute to AI-augmented DevOps initiatives MCP server/tool integration and multi-agent assistants on Azure AI Foundry / Azure OpenAI.</span></span></span> </li><li><span><span><span>Troubleshoot production incidents, optimize for performance and cost, and continuously improve platform engineering practices.</span></span></span> </li></ul> <span><span><span><strong><span><span>Must-Have Skills</span></span></strong></span></span></span> <br> <span><span><span><strong><span>Azure DevOps Suite</span></strong></span></span></span><br> <span><span><span>Deep hands-on experience with Azure Repos, Azure YAML Pipelines, Azure Artifacts, and Azure Test Plans, plus Azure DevOps REST APIs and extensions.</span></span></span><br> <span><span><span><strong><span>CI/CD &amp; Deployment</span></strong></span></span></span><br> <span><span><span>End-to-end pipelines for complex applications across all environments; GitHub Actions; blue-green and canary deployment strategies.</span></span></span><br> <span><span><span><strong><span>Azure Cloud Services</span></strong></span></span></span><br> <span><span><span>Production-grade experience across the Azure ecosystem, including APIM, Azure Front Door,App gateway and CDN.</span></span></span><br> <span><span><span><strong><span>Containerization &amp; Orchestration</span></strong></span></span></span><br> <span><span><span>Docker, Kubernetes (AKS), Helm, and GitOps delivery with ArgoCD or Flux. Service mesh experience (Istio / Linkerd) a strong plus.</span></span></span><br> <span><span><span><strong><span>Infrastructure as Code</span></strong></span></span></span><br> <span><span><span>Terraform (Azure provider, remote state in Azure Storage, Azure Verified Modules), ARM templates, and Azure Resource Graph.</span></span></span><br> <span><span><span><strong><span>DevSecOps</span></strong></span></span></span><br> <span><span><span>Security integrated into CI/CD, with tools such as SonarQube, HashiCorp Vault, and HP Fortify. Familiarity with SAST, DAST, SCA, container/image scanning, secret scanning, and policy-as-code.</span></span></span><br> <span><span><span><strong><span>Observability &amp; Monitoring</span></strong></span></span></span><br> <span><span><span>Azure Monitor, Application Insights, Log Analytics, Kusto Query Language (KQL), and Azure Workbooks. Experience with Prometheus, Grafana, Dynatrace, or the Elastic/Kibana stack is a plus.</span></span></span><br> <span><span><span><strong><span>FinOps &amp; Cost Optimization</span></strong></span></span></span><br> <span><span><span>Hands-on experience implementing FinOps practices and tooling to monitor, allocate, and optimize cloud spend.</span></span></span><br> <span><span><span><strong><span>Automation &amp; Scripting</span></strong></span></span></span><br> <span><span><span>PowerShell, Azure CLI, Azure PowerShell module, Python, and Bash.</span></span></span><br> <span><span><span><strong><span>Code Quality &amp; Version Control</span></strong></span></span></span><br> <span><span><span>Git, GitHub, Azure Repos, branching strategies (GitFlow, trunk-based development), and pull request policies.</span></span></span><br> <span><span><span><strong><span>Architecture &amp; Culture</span></strong></span></span></span><br> <span><span><span>Microservices and serverless architectures on Azure; strong grasp of Agile/DevOps culture, the Azure Well-Architected Framework, and the Cloud Adoption Framework.</span></span></span><br> <span><span><span><strong><span>AI / MLOps (advantageous)</span></strong></span></span></span><br> <span><span><span>Exposure to Azure AI Foundry, Azure Machine Learning, Azure OpenAI Service, and Azure AI Search — plus MCP server and MCP tool integration experience.</span></span></span> <span><span><span><strong><span><span>Nice to Have</span></span></strong></span></span></span> <br> <ul> <li><span><span><span>Certifications: Microsoft Certified DevOps Engineer Expert (AZ-400), Azure Solutions Architect Expert (AZ-305), Azure Administrator Associate (AZ-104), Azure Security Engineer Associate (AZ-500), FinOps Certified Practitioner, or Certified Kubernetes Security Specialist (CKS).</span></span></span> </li><li><span><span><span>Experience with Azure Landing Zones and enterprise-scale architectures.</span></span></span> </li><li><span><span><span>A track record of driving cost-awareness culture across engineering teams and partnering with finance stakeholders.</span></span></span> </li></ul> <span><span><span><strong><span><span>Why Join Us</span></span></strong></span></span></span> <br> <span><span><span>You'll join a strong platform engineering team operating a modern, Azure-native platform at real scale, with genuine ownership, autonomy, and room to shape both the infrastructure and the next generation of AI-augmented DevOps tooling. If you like solving hard production problems and building things properly, you will fit right in.</span></span></span><br> &nbsp; <br><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Mindrift is looking for skilled Bot Developers (WhatsApp Business API, Telegram Bot API, Discord API) to join the Tendem project (https://tendem.<br>ai/) and build conversational bots and messaging-platform integrations for real-world applications.<br> In this role, you'll use your bot engineering expertise, conversational design skills, and quality-focused approach to build reliable, useful bots and messaging integrations that deliver a great user experience.<br> This part-time remote opportunity is ideal for professionals with hands-on experience building messaging bots, working with platform APIs and webhooks, and implementing conversational logic.<br> What We Do The Mindrift platform connects specialists with innovative technology projects.<br> Our mission is to help develop high-quality AI technologies by combining real-world expertise from professionals across the globe with advanced AI development efforts.<br> About the Role This is a freelance role for a Tendem project.<br> As a Bot Developer, you'll design, build, and refine messaging bots for one or more messaging platforms, including WhatsApp, Telegram, Discord, Slack, and similar platforms — for use cases such as customer service, appointment booking, order taking, content delivery, moderation, and automated notifications.<br> Key Responsibilities Build bots for one or more messaging platforms, such as WhatsApp (Business API / Cloud API), Telegram (Bot API), Discord, Slack and similar messaging platforms.<br> Design and implement conversational flows, dialogue state, and fallback handling.<br> Integrate bots with LLMs (OpenAI, Anthropic, or similar) for natural language responses where appropriate.<br> Connect bots to backend services, databases, CRMs, and third-party APIs (booking systems, payment, content sources).<br> Handle webhooks, rate limits, and platform-specific message formats (interactive messages, buttons, media, templates).<br> Review, debug, optimize, and refactor bot implementations to improve correctness, reliability, maintainability, and graceful error handling.<br> Implement logging, monitoring, and recovery so bots stay healthy in production.<br> Requirements and benefits Educational qualifications At least 3 years of relevant experience backend, integration, automation, or bot development experience (required).<br> Bachelor's or Master's Degree in Computer Science, Engineering, Information Technology, or related technical fields is a plus.<br> Academic and/or Professional Experience Candidates should have a strong foundation in bot development, messaging platform integrations, and building reliable conversational workflows.<br> We are looking for specialists who can design and maintain production-ready bots, work confidently with APIs, webhooks, and backend services, and build stable, user-friendly bot experiences.<br> Strong problem-solving skills, attention to detail, and the ability to work independently are essential.<br> Technical Skills (Essential) At least 1 year of hands-on experience building bots for at least one major messaging platforms (WhatsApp, Telegram, Discord, Slack, or similar) is required Strong command of Python or Node.<br>js for backend bot logic.<br> Solid experience with REST APIs, webhooks, OAuth, and async request handling.<br> Experience with relational or NoSQL databases for storing conversation state and user data.<br> Familiarity with LLM APIs (OpenAI, Anthropic) and prompt design for conversational use is a strong plus.<br> Understanding of platform-specific limits, message templates, and approval flows (e.<br>g., WhatsApp template messages).<br> Experience with hosting and deployment (Docker, serverless, VPS, or PaaS) Additional requirements Strong attention to detail and commitment to bot reliability — no silent failures, no broken flows.<br> Self-directed work ethic with the ability to design and ship complete bots independently.<br> Portfolio or examples of bots you've built (required).<br> English proficiency: Upper-intermediate (B2) or above (required) Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements.<br> This is an estimate, not a guaranteed workload, and applies only while the project is active.<br> Compensation On this project, contributors can earn up to $60 per hour equivalent , depending on their level and pace of contribution.<br> Compensation varies across projects depending on scope, complexity, and required expertise.<br> Please note that other projects on the platform may offer different earning levels based on their requirements.<br> Why this freelance opportunity might be a great fit for you?<br> Work fully remote on your own schedule with just a laptop and stable internet connection.<br> Apply your expertise to real-world technology projects while gaining experience building high-quality solutions for a global platform.<br> Participate in performance-based bonus programs that reward high-quality work and consistent delivery.<br></span> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Company Description<br><p>Talabat is part of the Delivery Hero Group, the world’s pioneering local delivery platform, our mission is to deliver an amazing experience—fast, easy, and to your door. We operate in around 65 countries worldwide. Headquartered in Berlin, Germany. Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index.</p><br><br>Job Description<br><p><strong>ROLE SUMMARY</strong></p><br><p>The Logistics Integrity team protects talabat's rider marketplace by detecting, preventing and reducing rider fraud and misconduct at scale across our eight markets in the Middle East. As a Sr. Specialist in the Integrity team, you will own end-to-end a portfolio of high-impact rider misconduct behaviors, plus the cross-cutting programs that keep the team's detection and enforcement engine running as one system. You will translate integrity risk into detection rules, enforcement actions and measurable reductions, working in close partnership with Product, Operations, Customer Experience and country leadership. Your work is a direct enabler of one of talabat's most important operational priorities: making our rider network faster, fairer and more reliable for the millions of customers we serve across the region.</p><br><p><strong>WHAT’S ON YOUR PLATE?</strong></p><br><ul><li><p>Own a portfolio of high-impact rider misconduct behaviors end-to-end: define how each is measured, baseline its prevalence across countries and rider cohorts, run root-cause analysis, and identify and prioritize the levers that will reduce it.</p><br></li><li><p>Design and tune the detection rules and enforcement thresholds behind talabat's integrity systems, and manage the country-by-country rollout of each change across the region.</p><br></li><li><p>Run the enforcement operating loop: periodic enforcement waves, tracking of the worst offenders, false-positive review, per-country performance tracking, and regular re-tuning based on what the data shows.</p><br></li><li><p>Document how detection and enforcement flow end-to-end for every actively-managed behavior, identify gaps, broken handoffs and redundancies, propose fixes.</p><br></li><li><p>Own the tooling and operational hygiene layer of the team: workflow automation, tracker maintenance, and the critical infrastructure that keeps the detection &amp; enforcement systems running.</p><br></li><li><p>Expand the team's active integrity coverage over time by surfacing and prioritizing new misconduct patterns from the broader risk behaviors, and building the business case to bring them into active management.</p><br></li><li><p>Contribute owned-behavior performance into talabat's regional integrity KPIs and the team's executive reporting cadence.</p><br></li><li><p>Maintain audit-ready documentation for owned behaviors (detection logic, thresholds, enforcement rules, decision trails, false-positive handling) to support internal governance and public-company compliance requirements.</p><br></li><li><p>Partner cross-functionally with Product, Operations, Customer Experience and country leadership on lever execution and country rollouts; participate in the team's weekly cadence and quarterly reviews.</p><br></li></ul><br>Qualifications<br><p><strong>WHAT DID WE ORDER?</strong></p><br><ul><li><p>4 to 6 years in Trust and Safety, Fraud and Risk, Marketplace Operations, or Logistics Operations Analytics; tech-enabled or multi-market environments preferred.</p><br></li><li><p>Bachelor's degree in engineering, business, economics or equivalent practical experience.</p><br></li><li><p>Track record in at least one of: behavioral fraud detection, rule-based design, gig-economy fleet operations, or large-scale anti-abuse programs.</p><br></li><li><p>Comfort owning a problem end-to-end: measurement, root-cause analysis, solution design, execution, and re-measurement of impact.</p><br></li><li><p>Strong SQL fluency (BigQuery a plus); comfortable building dashboards and writing lightweight Python for automation.</p><br></li><li><p>Analytical depth: ability to move from anomaly, to root cause, to lever, to business case, to measured impact.</p><br></li><li><p>Process-mapping mindset: comfortable dissecting operational workflows and naming where they break.</p><br></li><li><p>Strong stakeholder management across Product, Operations and country teams; comfortable operating across multiple markets with different operational baselines and rule sets.</p><br></li><li><p>Comfort with threshold tuning and the trade-off between catching abuse and unfairly flagging genuine users.</p><br></li><li><p>Ability to influence, empower and align people across a broad variety of job functions.</p><br></li><li><p>Extremely organized and process-driven, able to manage internal workload and expectations across a large set of stakeholders.</p><br></li><li><p>Strong commitment to enforcing standards, ethics and compliance.</p><br></li><li><p>Hands-on, enjoys fact-finding and going beyond theoretical frameworks.</p><br></li><li><p>Strong fluency with Gen AI tools like Claude and Claude Code.</p><br></li><li><p>Excellent written and verbal communication skills in English.</p><br></li><li><p>Team player who thrives on comradery.</p><br></li></ul><br><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <br>About the opportunity<br><p><strong>ROLE SUMMARY</strong></p><br><br><p>The Logistics Integrity team protects talabat's rider marketplace by detecting, preventing and reducing rider fraud and misconduct at scale across our eight markets in the Middle East. As a Sr. Specialist in the Integrity team, you will own end-to-end a portfolio of high-impact rider misconduct behaviors, plus the cross-cutting programs that keep the team's detection and enforcement engine running as one system. You will translate integrity risk into detection rules, enforcement actions and measurable reductions, working in close partnership with Product, Operations, Customer Experience and country leadership. Your work is a direct enabler of one of talabat's most important operational priorities: making our rider network faster, fairer and more reliable for the millions of customers we serve across the region.</p><br><br><p><strong>WHAT’S ON YOUR PLATE?</strong></p><br><br><ul><li><p>Own a portfolio of high-impact rider misconduct behaviors end-to-end: define how each is measured, baseline its prevalence across countries and rider cohorts, run root-cause analysis, and identify and prioritize the levers that will reduce it.</p><br><br></li><li><p>Design and tune the detection rules and enforcement thresholds behind talabat's integrity systems, and manage the country-by-country rollout of each change across the region.</p><br><br></li><li><p>Run the enforcement operating loop: periodic enforcement waves, tracking of the worst offenders, false-positive review, per-country performance tracking, and regular re-tuning based on what the data shows.</p><br><br></li><li><p>Document how detection and enforcement flow end-to-end for every actively-managed behavior, identify gaps, broken handoffs and redundancies, propose fixes.</p><br><br></li><li><p>Own the tooling and operational hygiene layer of the team: workflow automation, tracker maintenance, and the critical infrastructure that keeps the detection &amp; enforcement systems running.</p><br><br></li><li><p>Expand the team's active integrity coverage over time by surfacing and prioritizing new misconduct patterns from the broader risk behaviors, and building the business case to bring them into active management.</p><br><br></li><li><p>Contribute owned-behavior performance into talabat's regional integrity KPIs and the team's executive reporting cadence.</p><br><br></li><li><p>Maintain audit-ready documentation for owned behaviors (detection logic, thresholds, enforcement rules, decision trails, false-positive handling) to support internal governance and public-company compliance requirements.</p><br><br></li><li><p>Partner cross-functionally with Product, Operations, Customer Experience and country leadership on lever execution and country rollouts; participate in the team's weekly cadence and quarterly reviews.</p><br><br></li></ul><br>What you need to be successful<br><p><strong>WHAT DID WE ORDER?</strong></p><br><br><ul><li><p>4 to 6 years in Trust and Safety, Fraud and Risk, Marketplace Operations, or Logistics Operations Analytics; tech-enabled or multi-market environments preferred.</p><br><br></li><li><p>Bachelor's degree in engineering, business, economics or equivalent practical experience.</p><br><br></li><li><p>Track record in at least one of: behavioral fraud detection, rule-based design, gig-economy fleet operations, or large-scale anti-abuse programs.</p><br><br></li><li><p>Comfort owning a problem end-to-end: measurement, root-cause analysis, solution design, execution, and re-measurement of impact.</p><br><br></li><li><p>Strong SQL fluency (BigQuery a plus); comfortable building dashboards and writing lightweight Python for automation.</p><br><br></li><li><p>Analytical depth: ability to move from anomaly, to root cause, to lever, to business case, to measured impact.</p><br><br></li><li><p>Process-mapping mindset: comfortable dissecting operational workflows and naming where they break.</p><br><br></li><li><p>Strong stakeholder management across Product, Operations and country teams; comfortable operating across multiple markets with different operational baselines and rule sets.</p><br><br></li><li><p>Comfort with threshold tuning and the trade-off between catching abuse and unfairly flagging genuine users.</p><br><br></li><li><p>Ability to influence, empower and align people across a broad variety of job functions.</p><br><br></li><li><p>Extremely organized and process-driven, able to manage internal workload and expectations across a large set of stakeholders.</p><br><br></li><li><p>Strong commitment to enforcing standards, ethics and compliance.</p><br><br></li><li><p>Hands-on, enjoys fact-finding and going beyond theoretical frameworks.</p><br><br></li><li><p>Strong fluency with Gen AI tools like Claude and Claude Code.</p><br><br></li><li><p>Excellent written and verbal communication skills in English.</p><br><br></li><li><p>Team player who thrives on comradery.</p><br><br></li></ul><br>Who we are<br><p>Talabat is part of the Delivery Hero Group, the world’s pioneering local delivery platform, our mission is to deliver an amazing experience—fast, easy, and to your door. We operate in around 65 countries worldwide. Headquartered in Berlin, Germany. Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index.</p><br><br> <br><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Mindrift is looking for skilled Bot Developers (WhatsApp Business API, Telegram Bot API, Discord API) to join the Tendem project (https://tendem.<br>ai/) and build conversational bots and messaging-platform integrations within our hybrid AI + human environment.<br> In this role, as an AI Pilot – that's how we refer to this position at Mindrift – you'll collaborate with Tendem Agents that handle repetitive tasks, while you provide bot engineering expertise, conversational design judgment, and quality control to ensure bots are reliable, useful, and ready for real users.<br> This part-time remote opportunity is ideal for professionals with hands-on experience building messaging bots, working with platform APIs and webhooks, and implementing conversational logic.<br> What We Do The Mindrift platform connects specialists with AI projects from major tech innovators.<br> Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.<br> About the Role This is a freelance role for a Tendem project.<br> As a Bot Developer, you'll design, build, and refine messaging bots for one or more messaging platforms, including WhatsApp, Telegram, Discord, Slack, and similar platforms — for use cases such as customer service, appointment booking, order taking, content delivery, moderation, and automated notifications.<br> Key Responsibilities Build bots for one or more messaging platforms, such as WhatsApp (Business API / Cloud API), Telegram (Bot API), Discord, Slack and similar messaging platforms.<br> Design and implement conversational flows, dialogue state, and fallback handling.<br> Integrate bots with LLMs (OpenAI, Anthropic, or similar) for natural language responses where appropriate.<br> Connect bots to backend services, databases, CRMs, and third-party APIs (booking systems, payment, content sources).<br> Handle webhooks, rate limits, and platform-specific message formats (interactive messages, buttons, media, templates).<br> Evaluate AI-generated bot code and refactor it for correctness, reliability, and graceful error handling.<br> Implement logging, monitoring, and recovery so bots stay healthy in production.<br> Requirements and benefits Educational qualifications At least 3 years of relevant experience backend, integration, automation, or bot development experience (required).<br> Bachelor's or Master's Degree in Computer Science, Engineering, Information Technology, or related technical fields is a plus.<br> Academic and/or Professional Experience Candidates should have a strong foundation in bot development, messaging platform integrations, and building reliable conversational workflows.<br> We are looking for specialists who can design and maintain production-ready bots, work confidently with APIs, webhooks, and backend services, and refine AI-assisted output into stable, user-friendly experiences.<br> Strong problem-solving skills, attention to detail, and the ability to work independently are essential.<br> Technical Skills (Essential) At least 1 year of hands-on experience building bots for at least one major messaging platforms (WhatsApp, Telegram, Discord, Slack, or similar) is required Strong command of Python or Node.<br>js for backend bot logic.<br> Solid experience with REST APIs, webhooks, OAuth, and async request handling.<br> Experience with relational or NoSQL databases for storing conversation state and user data.<br> Familiarity with LLM APIs (OpenAI, Anthropic) and prompt design for conversational use is a strong plus.<br> Understanding of platform-specific limits, message templates, and approval flows (e.<br>g., WhatsApp template messages).<br> Experience with hosting and deployment (Docker, serverless, VPS, or PaaS) Additional requirements Strong attention to detail and commitment to bot reliability — no silent failures, no broken flows.<br> Self-directed work ethic with the ability to design and ship complete bots independently.<br> Portfolio or examples of bots you've built (required).<br> English proficiency: Upper-intermediate (B2) or above (required).<br> Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements.<br> This is an estimate, not a guaranteed workload, and applies only while the project is active.<br> Compensation On this project, contributors can earn up to $60 per hour equivalent , depending on their level and pace of contribution.<br> Compensation varies across projects depending on scope, complexity, and required expertise.<br> Please note that other projects on the platform may offer different earning levels based on their requirements.<br> Why this freelance opportunity might be a great fit for you?<br> Work fully remote on your own schedule with just a laptop and stable internet connection.<br> Gain hands-on experience in a unique hybrid environment where human expertise and AI agents collaborate seamlessly — a distinctive skill set in a rapidly growing field.<br> Participate in performance-based bonus programs that reward high-quality work and consistent delivery.<br></span> </div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>About the Role</p><p>We are seeking a highly skilled engineer to deliver production-grade AI agents and business automations — systems</p><p>engineered for reliability, scale and sustained business value in live enterprise environments. You will build agents</p><p>and workflows that take real actions across enterprise applications - querying data, interpreting documents and</p><p>emails, executing multi-system workflows, and preparing business transactions - while supporting the company's</p><p>AI and analytics roadmap throughout the AI lifecycle: preparing and integrating enterprise data, evaluating AI</p><p>vendors, tools and solutions, ensuring AI governance compliance, and building internal awareness of emerging AI</p><p>technologies.</p><p>Key Responsibilities</p><ol><li><p>AI Agent Engineering &amp; System Architecture</p></li></ol><ul><li><p>Design, develop and deploy autonomous and multi-agent systems with planning, reasoning, tool use, memory</p></li></ul><p>and state management — via agentic frameworks or direct LLM API integrations.</p><ul><li><p>Deliver agents across pro-code and low-code tiers - Azure AI Foundry, LangChain and LangGraph and</p></li></ul><p>Microsoft Copilot Studio — selecting the right tier per use case.</p><ul><li><p>Define strict tool contracts and structured output schemas, integrating agents with enterprise applications via</p></li></ul><p>REST APIs and Model Context Protocol (MCP).</p><ul><li><p>Orchestrate multi-user, role-based agentic workflows with review-before-commit human approval before any</p></li></ul><p>write-back or dispatch, built as durable, long-running processes with persistent state and resumability.</p><ol><li><p>Business Process Automation &amp; Workflow Development</p></li></ol><ul><li><p>Analyze, document and redesign repetitive processes across Finance, Procurement, Sales, Production,</p></li></ul><p>Engineering, HR and IT, selecting the right automation approach for each.</p><ul><li><p>Design, build and deploy workflows in Power Automate — approvals, notifications, escalations, scheduled</p></li></ul><p>and event-driven processes triggered via APIs and webhooks.</p><ul><li><p>Build Copilot Studio custom agents with actions, topics, knowledge sources and custom connectors to</p></li></ul><p>enterprise applications, with error handling and logging built in.</p><ol><li><p>Retrieval Engineering (RAG)</p></li></ol><ul><li><p>Build and optimize Retrieval Augmented Generation pipelines: chunking, embedding selection, hybrid search</p></li></ul><p>and re-ranking over vector databases. Continuously measure and tune retrieval quality for relevance and</p><p>precision.</p><ol><li><p>Data Engineering &amp; Integration</p></li></ol><ul><li><p>Clean, integrate and validate data from ERP, production and data-warehouse environments; build ETL</p></li></ul><p>pipelines, data mapping and quality checks feeding AI initiatives.</p><ol><li><p>Document &amp; Email Automation</p></li></ol><ul><li><p>Automate extraction and validation of data from business documents and incoming emails using OCR and AI</p></li></ul><p>document intelligence, routing low-confidence cases for human review.</p><ol><li><p>Reliability, Evaluation &amp; Observability</p></li></ol><ul><li><p>Engineer agents and workflows to mission-critical standards retries with backoff, fallbacks and circuit</p></li></ul><p>breakers, plus error handling, production monitoring and root-cause analysis.</p><ul><li><p>Trace every tool call and reasoning step. Run metrics-driven test pipelines and dashboards tracking success</p></li></ul><p>rates, latency, cost and business benefits.</p><ol><li><p>Production Deployment</p></li></ol><ul><li><p>Deploy containerized services via CI/CD to Kubernetes behind an application gateway, with centralized</p></li></ul><p>monitoring, secrets management and asynchronous messaging.</p><ol><li><p>Security &amp; Safety</p></li></ol><ul><li><p>Defend agents against prompt injection with permission boundaries, input validation and output filters;</p></li></ul><p>enforce least-privilege access and full audit trails per AI governance and standard compliance policies.</p><ol><li><p>AI Project Coordination, Research &amp; Enablement</p></li></ol><ul><li><p>Gather and document AI use-case requirements; support UAT execution and issue management through go</p></li></ul><p>live.</p><ul><li><p>Track emerging AI technologies and propose POC and pilot projects.</p></li><li><p>Support employee training in responsible AI usage and prepare guidance and onboarding documentation.</p></li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p>Required Qualifications &amp; Skills</p><ul><li><p>Bachelor's degree in Computer Science, Software Engineering, IT, AI/ML or related discipline.</p></li><li><p>5+ years in software engineering, automation or system integration, including 2+ years building LLM-based</p></li></ul><p>agentic systems in production.</p><ul><li><p>Hands-on experience with agentic frameworks (LangChain, LangGraph, Microsoft Agent Framework or</p></li></ul><p>comparable) and LLM APIs (Azure OpenAI or similar): tool use, structured outputs, streaming, prompt and</p><p>context engineering.</p><ul><li><p>Practical experience building RAG pipelines with vector databases (pgvector, FAISS, Azure AI Search or</p></li></ul><p>similar).</p><ul><li><p>Hands-on experience with Power Automate and Copilot Studio, and integrating enterprise applications</p></li></ul><p>through REST APIs, JSON, webhooks and MCP.</p><ul><li><p>Strong Python; frontend development with React (Vite or similar tooling) for agent-facing user interfaces;</p></li></ul><p>Solid SQL and ETL / data pipeline development.</p><ul><li><p>Experience with Microsoft Azure services (AKS, Functions, Logic Apps, Service Bus, Key Vault, Azure OpenAI /</p></li></ul><p>AI Foundry) and containerized production deployment (Docker, Kubernetes, CI/CD) strongly preferred.</p><ul><li><p>Applied ML fundamentals — forecasting, classification, optimization, recommender systems — including</p></li></ul><p>statistical validation and anomaly detection on transactional business data is a strong plus.</p><ul><li><p>Understanding of business workflows, approvals, financial controls and exception handling; strong</p></li></ul><p>communication skills in English.</p><p></p></section>