Python Developer Jobs in UAE

<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 across WhatsApp, Telegram, Discord, 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 WhatsApp (Business API / Cloud API), Telegram (Bot API), Discord, 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 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>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>Field Engineering teams across AWS are building AI-enabled workflows to accelerate investigations, automate repetitive tasks, improve reporting, and develop scalable engineering tooling. These efforts are happening organically — driven by motivated engineers across regions. The opportunity now is to systematically scale what's working and embed dedicated AI integration capability directly within each regional Field Engineering team.<br>The Forward Deployed AI Integrator will be 100% focused on AI integration for their assigned region. This role embeds directly with regional FE teams to identify high-value workflow opportunities, drive hands-on adoption of AI-assisted tooling, and convert successful experiments into repeatable regional standards. The role partners with FE engineers, regional leads, and cross-functional GenAI platform teams to deliver measurable productivity outcomes within the region.<br>This is a hands-on execution role — not advisory. Success is measured by workflows transformed, engineering hours saved, and adoption driven within the region.<br>Key job responsibilities<br>Embed directly with regional Field Engineering teams to identify, prioritize, and accelerate the highest-value AI workflow opportunities<br>Drive adoption of AI-assisted workflows across investigations, reporting, operational analysis, and engineering tooling within the assigned region<br>Partner with FE engineers to replace manually intensive workflows with scalable, reusable AI-enabled solutions<br>Build and document reusable workflow patterns, templates, and lightweight operational playbooks for regional FE adoption<br>Work with GenAI platform teams and internal tooling teams to accelerate delivery of FE AI initiatives within approved deployment environments<br>Coach and enable FE engineers on practical, approved AI tools including Python-based tooling, Kiro, and internal AI platforms<br>Track and report adoption metrics and operational KPIs to regional and senior FE leadership<br>Identify opportunities to eliminate duplicated effort and share reusable capabilities across regional FE teams<br>Contribute to the broader FE AI integration community by sharing learning, patterns, and outcomes across regions<br>Support development of FE-led initiatives including waveform analytics, reporting automation, engineering tooling, and operational dashboards<br>A day in the life<br>You are embedded in the regional Field Engineering team — working alongside engineers during live investigations, building automation patterns, and coaching ICs on workflow adoption. You spend your time identifying what's slowing engineers down, prototyping AI-assisted solutions, and driving adoption of what works.<br>You are a dedicated member of the regional team, accountable for making AI integration real and measurable. You bring technical depth, operational curiosity, and a bias for action. You move fast, learn from what you build, and share what works with the broader FE AI integration community.<br>You are known in your region as the person who makes AI practical — and delivers it.<br>About the team<br>Field Engineering supports critical operational functions across global AWS infrastructure. The organization spans multiple engineering disciplines and regions — covering operational investigations, electrical and mechanical systems, tooling development, reporting, commissioning, troubleshooting, operational analytics, and process improvement.<br>The team is actively building AI-enabled workflows to improve operational efficiency and accelerate engineering execution. This role is one of three initial regional AI integration positions, designed to prove the model and scale it across all FE regions.<br>- Bachelor's degree or above in ML Engineering, Computer Science, Data Science, or a related technical discipline — or equivalent practical experience<br>- 3+ years of experience in technical program management, workflow automation, or operational analytics<br>- Experience with GenAI platforms, agentic tooling, or AI-enabled operational workflows<br>- Experience within large-scale infrastructure, operational engineering, or data center environments<br>- Experience embedding with operational teams to drive hands-on workflow transformation<br>- Experience in engineering investigations, reporting automation, or workflow acceleration initiatives<br>- Experience working in or supporting EMEA Region and other regions globally.<br>- Demonstrated ability to drive adoption and change within a technical team without direct authority<br>- Strong written and verbal communication skills, with the ability to clearly articulate impact and progress to engineering and leadership audiences<br>Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.</p><br> </div>

At Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.<br><br>You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.<br><br><strong>About The Role<br><br></strong>We are seeking a Senior Data Intelligence MLOps Engineer to design, build, and maintain the backbone of our Machine Learning lifecycle. You will be responsible for the "industrialization" of AI, moving models from experimental notebooks into robust, production-grade pipelines. Your mission is to automate the journey from raw data curation to model deployment, ensuring our CI/CD cycles are fast, observable, and reproducible.<br><br><strong>Key Responsibilities<br><br></strong><ul><li>End-to-End Pipeline Orchestration: Build and manage automated workflows for data preparation, feature engineering, model training, and evaluation.</li><li>Machine Learning CI/CD/CT Implementation: Develop Continuous Integration (code testing), Continuous Deployment (model serving), and Continuous Training (retraining triggers) systems.</li><li>Infrastructure as Code (IaC): Manage scalable Machine Learning infrastructure using tools like MLFlow</li><li>Model Monitoring &amp; Observability: Implement dashboards and alerts for model drift, data skew, and system performance (latency/throughput).</li><li>Registry Management: Maintain the Model Registry and Feature Store to ensure versioning and lineage across all experiments.</li><li>Security &amp; Compliance: Ensure data privacy and secure access controls throughout the ML lifecycle.<br><br><br></li></ul><strong>About you<br><br></strong><ul><li>5+ years in DevOps, Data Engineering, or MLOps roles.</li><li>Proven Track Record: of taking at least one ML project from a research phase to a high-availability production environment.</li><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field. </li><li>Orchestration Tools: Expertise in Kubeflow, Airflow, Dagster, or Prefect.</li><li>Containerization: Mastery of Docker and Kubernetes (K8s) for managing distributed training and inference.</li><li>Cloud Platforms: Deep experience with AWS (SageMaker), GCP (Vertex AI), or Azure ML.</li><li>Version Control: Advanced Git workflows and experience with DVC (Data Version Control) or MLflow.</li><li>CI/CD Frameworks: Experience with GitHub Actions, GitLab CI, or Jenkins specifically for ML artifacts.</li><li>Scripting: High proficiency in Python and Bash for automation.<br><br><br></li></ul>Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.

<strong>About Us<br><br></strong>At Dyson, we’re driven by a relentless pursuit of innovation—pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson’s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.<br><br>You’ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.<br><br><strong>About The Role<br><br></strong>We are seeking Data Intelligence MLOps Engineer to design, build, and maintain the backbone of our Machine Learning lifecycle. You will be responsible for the "industrialization" of AI, moving models from experimental notebooks into robust, production-grade pipelines. Your mission is to automate the journey from raw data curation to model deployment, ensuring our CI/CD cycles are fast, observable, and reproducible.<br><br><strong>Key Responsibilities<br><br></strong><ul><li>End-to-End Pipeline Orchestration: Build and manage automated workflows for data preparation, feature engineering, model training, and evaluation.</li><li>Machine Learning CI/CD/CT Implementation: Develop Continuous Integration (code testing), Continuous Deployment (model serving), and Continuous Training (retraining triggers) systems.</li><li>Infrastructure as Code (IaC): Manage scalable Machine Learning infrastructure using tools like MLFlow</li><li>Model Monitoring &amp; Observability: Implement dashboards and alerts for model drift, data skew, and system performance (latency/throughput).</li><li>Registry Management: Maintain the Model Registry and Feature Store to ensure versioning and lineage across all experiments.</li><li>Security &amp; Compliance: Ensure data privacy and secure access controls throughout the ML lifecycle.<br><br><br></li></ul><strong>About you<br><br></strong><ul><li>3+ years in DevOps, Data Engineering, or MLOps roles.</li><li>Proven Track Record: of taking at least one ML project from a research phase to a high-availability production environment.</li><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field. </li><li>Orchestration Tools: Expertise in Kubeflow, Airflow, Dagster, or Prefect.</li><li>Containerization: Mastery of Docker and Kubernetes (K8s) for managing distributed training and inference.</li><li> Cloud Platforms: Deep experience with AWS (SageMaker), GCP (Vertex AI), or Azure ML.</li><li>Version Control: Advanced Git workflows and experience with DVC (Data Version Control) or MLflow.</li><li>CI/CD Frameworks: Experience with GitHub Actions, GitLab CI, or Jenkins specifically for ML artifacts.</li><li>Scripting: High proficiency in Python and Bash for automation.<br><br><br></li></ul>Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.

<p><strong>Data Engineer / Data Analyst / Data Analytics (B2C Digital Platform)- Onsite - Dubai</strong></p><p><br></p><p><strong>Company Overvivew:</strong></p><p><br></p><p>UAE-based pioneer delivering customer-centric experiences and unparalleled opportunities through cutting-edge technology, with six innovative tech ventures across the globe.</p><p><br></p><p><strong>Role Overview:</strong></p><p>We are seeking a strategic, analytical, and business-savvy Data Analytics and Business Intelligence to mana our analytics and BI function. This role is responsible for developing and executing analytics strategies, implementing advanced BI solutions, and delivering actionable insights that improve performance, efficiency, and growth.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><p><br></p><p><strong>Strategic Leadership:</strong></p><ul><li>Define and execute the data analytics and BI roadmap aligned with business goals.</li><li>Collaborate with senior leadership to identify key metrics and decision-making needs.</li><li>Evangelize data-driven culture across the organization.</li></ul><p><br></p><p><strong>Team &amp; Project Management:</strong></p><ul><li>Manage prioritization of analytics projects and ensure timely delivery of insights.</li><li>Oversee the development, deployment, and maintenance of dashboards and reports.</li></ul><p><br></p><p><strong>Data &amp; Insights Delivery</strong></p><ul><li>Translate complex data into actionable business insights and strategic recommendations.</li><li>Perform exploratory, predictive, and prescriptive analytics to solve business problems.</li><li>Ensure data accuracy, quality, and governance in all reporting and analytics processes.</li></ul><p><br></p><p><strong>BI Tools &amp; Infrastructure:</strong></p><ul><li>Own the strategy and optimization of BI platforms <strong>(e.g., Power BI, Tableau, Looker).</strong></li><li>Collaborate with Data Engineering to maintain scalable data pipelines and infrastructure.</li><li>Drive automation and self-service analytics capabilities across business units.</li></ul><p><br></p><p><strong>Cross-functional Collaboration:</strong></p><ul><li>Partner with stakeholders in Sales, Marketing, Finance, Product, and Operations.</li><li>Understand departmental KPIs and provide data support to improve performance.</li><li>Present key findings to executive leadership and recommend course of action.</li></ul><p><br></p><p><strong>Qualifications:</strong></p><p><strong>Education:</strong></p><ul><li>Bachelor's degree in Computer Science, Data Science, Statistics, Business, or related field.</li><li>Masters degree or MBA preferred.</li></ul><p><br></p><p><strong>Experience:</strong></p><ul><li>8+ years of experience in data analytics or business intelligence roles.</li><li>Experience in managing cross-functional analytics initiatives.</li></ul><p><br></p><p><strong>Technical Skills:</strong></p><ul><li>Proficiency in <strong>SQL, Python, or R for data analysis.</strong></li><li>Expertise in BI tools (<strong>e.g., Power BI, Tableau, Qlik, Looker).</strong></li><li>Experience with data warehousing solutions (<strong>e.g., Snowflake, Redshift, BigQuery).</strong></li><li>Strong understanding of <strong>data modeling, ETL processes, and cloud data platforms.</strong></li></ul><p><br></p><p><strong>Other Details:</strong></p><p><br></p><p><strong>Work Mode: Onsite - Full Time</strong></p><p><strong> Location: Al safa Dubai, UAE</strong></p><p><strong>Experience: 8 to 10 years years</strong></p><p><strong>Days: Monday to Friday</strong></p><p><strong>Timing: 9am-6pm</strong></p><p><br></p><p><strong>Benefits:</strong></p><ul><li>Health insurance for employee &amp; family</li><li>Annual Ticket</li><li>24 Annual leaves on year completion</li><li>Bonus - performance based</li><li>Annual increment</li></ul><p><br></p><p><strong>About HR Ways</strong></p><p>HR Ways is an award-winning Technical Recruitment Firm helping software houses and IT Product companies internationally and locally to find IT Talent. HR Ways is engaged by 300+ Employers worldwide, ranging from the world’s biggest SaaS Companies to the most competitive Startups. We have entities in Dubai, Canada, the US, the UK, Pakistan, India, Saudi Arabia, Portugal, Brazil, and other parts of the world. Join our WhatsApp Channel <u>https://whatsapp.com/channel/0029VamSiLr5fM5fMtAdCS2M</u> to stay updated, or visit <u>www.hrways.co</u> to know more.</p>

<strong>Overview<br><br></strong><strong>About Analog<br><br></strong>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.<br><br>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<br><br>As a <strong>Sr. Research Engineer</strong>, you will be responsible for building AI systems that can perform previously improbable tasks or achieve unprecedented levels of performance. We're looking for people with solid engineering skills (for example designing, implementing, and improving a massive-scale distributed machine learning system), writing bug-free machine learning code, and building the science behind the algorithms employed. The most outstanding deep learning results are increasingly attained at a massive scale, and these results require engineers who are comfortable working in large distributed systems.<br><br><strong>Responsibilities<br><br></strong><ul><li>Past experience in creating high-performance implementations of deep learning algorithms</li><li>Have experience working in large distributed systems</li><li>Provide technical perspective to develop ML best practices and influence engineering culture in the team</li><li>Have in depth knowledge of how the machine learning system interacts with systems around it</li><li>Evaluate the tradeoffs of different ML models/systems and deploy best ML practices</li><li>Experience with Data/Feature Engineering, Training, Evaluation and Deployment of ML models<br><br></li></ul><strong>Qualifications<br><br></strong><ul><li>Have run at least small-scale ML experiments</li><li>Love figuring out how systems work and continuously come up with ideas for how to make them faster while minimizing complexity and maintenance burden</li><li>Have strong software engineering skills and are proficient in Python</li><li>Comfortable working with researchers to enable them to develop the next generation of models<br><br></li></ul><strong>What Working At Analog Offers<br><br></strong><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.<br><br></li></ul><strong>If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.</strong>

<p><strong><u>Principal AI Ops Engineer – Abu Dhabi</u></strong></p><p><strong><u>Discover the Opportunity:</u></strong></p><p>We’re partnering with a leading organisation in Abu Dhabi that is building and operating advanced AI systems at significant scale.</p><p><br></p><p>They’re looking for a <strong>Principal AI Ops Engineer</strong> to take ownership of how AI and LLM systems operate in production, covering inference and model serving, deployment, observability, reliability and performance.</p><p><br></p><p>This is a Principal-level individual contributor role for someone who combines deep AI infrastructure expertise with strong software and reliability engineering fundamentals. You’ll set the operational standards that allow engineering teams to deploy and run production AI systems safely, reliably and efficiently.</p><p><br></p><p><strong><u>Discover the Responsibilities:</u></strong></p><ul><li>Design, operate and optimise GPU-based inference and model-serving infrastructure for production AI and LLM workloads. </li><li>Optimise model serving across latency, throughput, batching, quantisation, autoscaling and infrastructure cost. </li><li>Build automated release pipelines for models, prompts and agent configurations, including canary deployments, regression gates and rollback strategies. </li><li>Establish AI-specific observability across model, retrieval and orchestration layers, including tracing, latency, cost and quality monitoring. </li><li>Define and maintain SLOs across availability, latency and AI system quality, alongside automated alerting and incident response processes. </li><li>Own capacity planning and cost optimisation across GPU and AI infrastructure. </li><li>Build secure, scalable Kubernetes environments and Infrastructure-as-Code patterns for production AI workloads. </li><li>Develop reusable deployment patterns, tooling and operational standards that enable engineering teams to ship AI systems reliably. </li><li>Lead complex production incidents, load testing and root-cause analysis across AI infrastructure and applications. </li><li>Provide technical leadership and help establish engineering standards for operating AI systems at scale. </li></ul><p><br></p><p><strong><u>Discover the Requirements:</u></strong></p><ul><li>Proven experience operating at <strong>Staff, Principal or equivalent senior IC level</strong>, with a track record of running production ML or LLM systems at scale. </li><li>Deep hands-on experience with <strong>GPU-based inference and model serving</strong>, including technologies such as vLLM, TGI, TensorRT-LLM or similar. </li><li>Strong understanding of batching, quantisation, latency, throughput, autoscaling and the performance trade-offs involved in production LLM serving. </li><li>Strong experience with <strong>AI/LLM observability</strong>, including tracing, quality monitoring, drift and regression detection. </li><li>Strong reliability engineering fundamentals across SLOs, incident response, capacity planning and post-mortems. </li><li>Strong Python engineering skills with experience building production-grade automation and infrastructure tooling. </li><li>Deep experience with <strong>Kubernetes, Docker and Infrastructure as Code</strong>, ideally Terraform, across cloud environments. </li><li>Experience with observability technologies such as <strong>Langfuse, LangSmith, Arize Phoenix, Grafana or Prometheus</strong>. </li><li>Experience integrating AI evaluation and regression testing into CI/CD and production release processes. </li><li>Experience with cloud infrastructure, ideally <strong>Azure</strong>, and production environments with strong security, data residency or compliance requirements. </li><li>Experience with GPU/AI infrastructure cost optimisation and FinOps would be advantageous. </li><li>A highly hands-on approach, with the ability to set technical standards while remaining close to engineering and production systems.</li></ul>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>Amazon Supply Chain team is looking for a talented, innovative, hands-on and customer-obsessed candidate for managing the capacity operations for AMET (Africa, Middle East &amp; Turkey) region.<br>The ideal candidate will be enthusiastic about managing challenging, lengthy projects across multiple teams and locations. We are looking for a Business Analyst who shares Amazon's passion for the customer—someone who understands the Engineering and Business both. This role requires an individual with excellent understanding of SQL and query development, good business acumen and the ability to work with business, program and product teams. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment, and driven by a desire to innovate in this space.<br>To be successful in this role you should have superior communication, presentation and organizational skills. Operating in a fast-moving and sometimes ambiguous environment you will work autonomously taking control and responsibility for achieving the objectives of the role. This role provides opportunities to develop original ideas, approaches, and solutions in a competitive and ever changing business climate.<br>As part of our commitment to complying with national labor laws and applicable legislations in the United Arab Emirates, this position is open to candidates who fulfill the specific nationality criteria stipulated by local regulations.<br>Key job responsibilities<br>1. Data analysis by writing ETL queries in SQL/Datanet platforms<br>2. Highly proficient with MS Excel<br>3. Enabling effective decision making by retrieving and aggregating data from multiple sources and compiling it into a digestible and actionable format<br>4. Analyzing and solving business problems with focus on understanding root causes and driving forward-looking opportunities<br>5. Designing new metrics and enhance existing metrics to support the future state of business processes and ensure sustainability<br>6. Understanding tools and processes and driving seller adoption<br>7. Communicating complex analysis and insights to stakeholders and business leaders, both verbally and in writing.<br>- Bachelor's degree, or BS degree<br>- Knowledge of SQL/ETL<br>- Knowledge of Excel at an advanced level<br>- Experience with data analytics platforms (Power BI, Python, SQL, Tableau), or experience in solving complex business challenges by delivering accurate and timely financial models, analysis, and recommendations that have a proven impact on business (e.g., financial savings, operational improvements, or customer benefits)<br>Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.</p><br> </div><h2 data-automation-id="subHeaderPreferredCandidate" class="h5"> Preferred candidate </h2> <div class="row is-m v-align-top t-small bg-mute"> <div class="col is-3 p5" data-automation-id="label_Nationality"> <b>Nationality</b> </div> <div class="col is-9 p5" data-automation-id="data_Nationality"> United Arab Emirates </div> </div>

<p><strong>Khazna was founded in 2012 and has grown rapidly into becoming the leading and trusted wholesale Data Center provider in the Middle East and North Africa region. Through our Data Centers, we provide industry benchmark levels of power supply and cooling services to better serve the growing need for data center operations in the UAE and wider region.</strong></p><p><br></p><p>We are seeking a <strong>Site Reliability Engineer</strong> to support the reliability engineering program across multiple data centers in our fleet. Reporting to the Reliability Manager, you will be responsible for monitoring system performance, driving preventative and predictive maintenance initiatives, leading root cause analysis efforts, and collaborating with cross-functional teams to minimize downtime and enhance infrastructure resilience.</p><p><br></p><p><strong>Key Accountabilities:</strong></p><p><br></p><ul><li>Monitor real-time and historical performance metrics for critical power, cooling, and IT systems.</li><li>Analyse system data to identify trends, failure modes, and reliability risks.</li><li>Execute Root Cause Analyses (RCA) and Failure Mode &amp; Effects Analyses (FMEA), then drive corrective and preventive actions.</li><li>Develop and maintain condition-based and predictive maintenance routines, leveraging IoT, data analytics, and machine learning tools.</li><li>Support preventive maintenance programs: schedule, document, and validate maintenance activities.</li><li>Assist in asset lifecycle planning, including upgrades, decommissioning, and end-of-life strategies.</li><li>Contribute to capacity runway assessments to forecast infrastructure needs.</li><li>Implement and enforce availability management plans, risk assessments, and mitigation strategies.</li><li>Ensure data collection and reporting processes for reliability KPIs (e.g., MTBF, MTTR, availability) are standardized and accurate.</li><li>Prepare reliability reports and dashboards; present findings and recommendations to site leadership.</li><li>Respond to and lead failure-response efforts during site incidents, ensuring rapid recovery and root-cause follow-through.</li><li>Maintain compliance with industry standards and regulations (Uptime Institute, ISO, ASHRAE).</li><li>Collaborate with Operations, Engineering, Facilities, and Vendors to integrate reliability best practices into day-to-day workflows.</li><li>Propose continuous-improvement initiatives and pilot emerging reliability technologies.</li><li>The job holder may be required to undertake additional duties, which may be reasonably expected and forms part of the function of the job.</li></ul><p><br></p><p><strong>Minimum Qualifications:</strong></p><p><br></p><ul><li>Bachelor’s degree in mechanical, Electrical, Reliability, or related Engineering discipline.</li></ul><p><br></p><p><strong>Minimum Experience:</strong></p><p><br></p><ul><li>3+ years of experience in reliability engineering, maintenance engineering, or a data center operations environment.</li><li>Hands-on experience with RCA, FMEA, and predictive maintenance methodologies.</li><li>Proficiency with monitoring platforms, data-analytics tools, and scripting (e.g., Python, R).</li><li>Familiarity with IoT sensors, machine-learning frameworks, and condition-based monitoring systems.</li><li>Knowledge of industry reliability standards and regulations (ISO, ASHRAE, Uptime Institute).</li></ul><p><br></p><p><strong>Job-Specific Skills (Generic / Technical):</strong></p><p><br></p><ul><li>Strong analytical and problem-solving skills, with acute attention to detail.</li><li>Effective communicator, able to present technical findings to diverse audiences.</li><li>Project coordination skills and the ability to manage multiple reliability initiatives.</li><li>Collaborative mindset, comfortable working in cross-functional teams.</li><li>Self-starter with a continuous-improvement attitude and commitment to resilience.</li></ul><p><br></p>

<ul><li><p>Take ownership of production issues across our platforms, including extended-hours and on-call coverage on a rotation.</p></li><li><p>Investigate issues across partners, from first symptom toward root cause.</p></li><li><p>Search and analyse production logs, cutting through noise to isolate the relevant events.</p></li><li><p>Read and navigate existing codebases to diagnose logic-level issues — such as concurrency, data-consistency, or integration bugs — and propose or implement targeted, well-tested fixes in collaboration with Engineering.</p></li><li><p>Resolve within your scope — including small, well-tested code-level fixes where appropriate — and escalate to the Support Lead with full evidence when a change is architecturally significant or the root cause is unclear.</p></li><li><p>Triage and manage tickets in Jira, keeping issues moving, chasing owners, and keeping stakeholders informed.</p></li><li><p>Write clear bug and change tickets and RCA/postmortem documentation, covering observed behaviour, evidence, suspected root cause, and references, so escalated issues arrive well-documented.</p></li><li><p>Monitor platform and transaction health and flag anomalies (timeouts, retries, duplicate disbursements, velocity-control rejections) before they escalate.</p></li><li><p>Communicate findings clearly to technical and non-technical audiences, without overstating what the evidence supports.</p></li></ul><p><strong>Desired Candidate Profile</strong></p><p><u>Must have</u></p><ul><li><p>6+ years prior experience in technical issue resolution in a fast-paced global support team.</p></li><li><p>3+ years of hands-on software development experience (Java, Python, or similar) — either before transitioning into support/operations, or alongside it — with real exposure to the SDLC: writing, testing, and shipping code, not just reading about it.</p></li><li><p>Comfortable reading an unfamiliar codebase, diagnosing a logic-level bug (e.g. a concurrency or data-consistency issue), and implementing a small, safe fix under guidance — this role does not involve building new features, but it does involve adjusting existing code.</p></li><li><p>Strong understanding of APIs and experience using Postman (or equivalent tools) for endpoint inspection and testing.</p></li><li><p>Proficient in SQL for querying and validating data across multiple databases (MariaDB, PostgreSQL, or similar).</p></li><li><p>General familiarity with web applications, microservices, and RESTful architectures.</p></li><li><p>Comfortable working with logs, monitoring tools, and error tracking systems.</p></li><li><p>Analytical mindset and strong troubleshooting skills; able to isolate problems quickly and propose next steps.</p></li><li><p>Excellent communication skills with excellent written and verbal English to collaborate effectively with both Customer Support (non-technical) and Engineering (technical) teams.</p></li><li><p>Experience writing RCA/postmortem documentation and communicating incident status to both technical and non-technical stakeholders.</p></li><li><p>A structured, evidence-first troubleshooting mindset that verifies across sources before declaring a root cause.</p></li><li><p>Sound escalation judgment; knows what to resolve and what to hand up.</p></li></ul><br><p><u>Nice to have</u></p><ul><li><p>Prior experience as a Software / Backend Engineer before moving into a support, SRE, or production-operations role.</p></li><li><p>Understanding of REST APIs, distributed systems, databases, and developer tools.</p></li><li><p>Familiarity with SQL, Postman, Kibana, Jira, and Confluence.</p></li><li><p>Comfortable with git-based workflows (branching, pull requests, code review) for small fixes.</p></li></ul>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>The Solutions Engineering team is a specialized team that is in control of the relationship between TikTok advertising clients. The team is looking for engineers with an entrepreneurial mindset and the voice of the market. The team is made up of creative problem solvers and strategic software engineers who work with clients to understand their problems and develop solutions. We work at the intersection of business and engineering to assist TikTok's marketing and advertising partners to flourish and achieve their business goals by developing technology solutions that fit their demands. As a Lead Solution Engineer, you will help to partner with different business verticals and enable the full potential of new features, products, and business opportunities. You will be working and supporting cross-functional teams of R&amp;D, Customer Success, and Product Management. This role allows you to use TikTok's platforms and community to solve real-world business problems. Responsibilities: - Lead the design and development of scalable, production-grade solutions in collaboration with TikTok Product Engineering teams to meet evolving business and client needs. - Act as a technical leader and subject matter expert across the Solutions Engineering organization, providing architectural guidance and driving engineering excellence. - Understand, apply and use TikTok's products and innovative technology, identify, develop, and maximize new and existing commercial prospects with advertising clients. - Cultivate close partnerships with the customer success team to identify potential business opportunities and support them in achieving business goals. - Design and build end-to-end systems and launch-plan strategies; launch production-level code, with an emphasis on long-term maintainability and scalability with applicable documentation and test plans, in collaboration with cross-functional teams. - Identify stakeholders independently and align cross-functional partners toward project completion goals. - Build and cultivate relationships with internal and external stakeholders. - Using Data to influence decision-making through the presentation of business value and impact. Minimum Qualifications: - Bachelor's degree or above, majoring in Computer Science or related fields - 5+ years of experience in software development, technical solutions design and delivery - 3+ years of experience in a technical leadership role - Familiarity with one or more general-purpose programming languages (e.g. Python, Go, Java, C/C++) and API/backend systems design - Hands-on experience with ML infrastructure (e.g., production model training and deployment, model evaluation, tuning/optimization, data pipeline processing, and debugging production issues). - Demonstrated ability to tailor your presentation to the audience's technical level and comfort delivering technical subjects to groups of any size or background - Experience in advertising technology working with large volume data analytics. Preferred Qualifications: - Experience with mobile application development and advertising across iOS/Android - Experience with machine learning frameworks and libraries such as TensorFlow or Keras</p> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><span><span><strong>Location: Abu Dhabi, UAE&nbsp;</strong></span></span></p><br><br> <p><span><span>Join a technology-driven organization building and operating mission-critical digital platforms that serve large-scale internal and customer-facing services.<br> <br> We are seeking a hands-on DevOps Specialist to help design, automate, secure, and operate modern cloud-native platforms. This role is ideal for engineers who enjoy solving complex infrastructure challenges, building scalable automation, improving developer experience, and ensuring platform reliability at scale.<br> <br> This position offers the opportunity to work with modern cloud technologies, Kubernetes platforms, Infrastructure-as-Code, DevOps automation, and production-grade systems within a highly collaborative engineering environment.</span></span></p><br><br> <p><strong><span><span>What You'll Be Doing</span></span></strong></p><br><br> <ul> <li><span><span>Design, build, automate, and support cloud-native infrastructure and platforms.</span></span> </li><li><span><span>Manage and improve Kubernetes environments across production and non-production systems.</span></span> </li><li><span><span>Develop and maintain Infrastructure-as-Code using Terraform and related tooling.</span></span> </li><li><span><span>Design, implement, and optimize CI/CD pipelines and deployment automation.</span></span> </li><li><span><span>Support containerized workloads using Docker and Kubernetes.</span></span> </li><li><span><span>Implement GitOps, automation, and platform engineering best practices.</span></span> </li><li><span><span>Monitor platform health, reliability, availability, and performance using modern observability solutions.</span></span> </li><li><span><span>Troubleshoot complex production incidents and perform root cause analysis.</span></span> </li><li><span><span>Collaborate with software engineering teams to improve deployment reliability, security, scalability, and developer experience.</span></span> </li><li><span><span>Improve operational excellence through automation, self-service capabilities, and continuous improvement initiatives.</span></span> </li><li><span><span>Contribute to platform security, governance, and cloud operational standards.</span></span> </li></ul> <p><strong><span><span>Required Qualifications</span></span></strong></p><br><br> <ul> <li>Must be <strong>immediately available, no notice period and within the UAE.&nbsp;</strong> </li><li><span><span>Minimum <strong>5 years of hands-on DevOps, SRE, Platform Engineering, Cloud Engineering, or Infrastructure Engineering experience</strong>.</span></span> </li><li><span><span>Minimum <strong>3 years of hands-on Kubernetes administration and operations experience</strong>.</span></span> </li><li><span><span>Bachelor's degree in Computer Science, Engineering, Information Technology, or related discipline.</span></span> </li><li><span><span>Strong Linux systems administration and troubleshooting skills.</span></span> </li><li><span><span>Hands-on experience with:</span></span> <ul> <li><span><span>Kubernetes</span></span> </li><li><span><span>Docker</span></span> </li><li><span><span>Terraform</span></span> </li><li><span><span>Git</span></span> </li><li><span><span>CI/CD platforms</span></span> </li><li><span><span>Cloud infrastructure</span></span> </li></ul> </li><li><span><span>Experience supporting <strong>production environments and critical business</strong> applications.</span></span> </li><li><span><span>Experience building automation solutions using Python, Bash, Shell scripting, or similar languages.</span></span> </li><li><span><span>Strong understanding of Infrastructure-as-Code principles and cloud-native architectures.</span></span> </li><li><span><span>Financial services, fintech, banking, telecommunications, or other highly regulated environments</span></span> </li></ul> <p><strong><span><span>Preferred Qualifications</span></span></strong></p><br><br> <p><span><span>Experience in one or more of the following:</span></span></p><br><br> <ul> <li><span><span>AWS, Azure, or GCP</span></span> </li><li><span><span>GitLab CI/CD, GitHub Actions, Azure DevOps, Jenkins</span></span> </li><li><span><span>GitOps platforms such as ArgoCD or Flux</span></span> </li><li><span><span>Helm</span></span> </li><li><span><span>Prometheus, Grafana, ELK/OpenSearch, Loki, Datadog, New Relic, Splunk</span></span> </li><li><span><span>Karpenter, KEDA, Istio, Service Mesh technologies</span></span> </li><li><span><span>DevSecOps practices and security automation</span></span> </li><li><span><span>Terraform Associate, CKA, CKAD, AWS/Azure/GCP certifications</span></span> </li></ul> <p><strong><span><span>What We're Looking For.&nbsp;</span></span></strong><span><span>We are particularly interested in engineers who:</span></span></p><br><br> <ul> <li><span><span>Remain highly hands-on technically.</span></span> </li><li><span><span>Have managed Kubernetes platforms in real production environments.</span></span> </li><li><span><span>Enjoy solving infrastructure and reliability challenges.</span></span> </li><li><span><span>Have built CI/CD and automation solutions from the ground up.</span></span> </li><li><span><span>Take ownership of platform stability, operational excellence, and engineering quality.</span></span> </li><li><span><span>Thrive in collaborative, fast-moving environments.</span></span> </li></ul> <p><span><span>#LI-JS1</span></span></p><br><br> <br><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><b>Overview of the role</b></p><p>The PMO Analyst will support project and portfolio management activities across the business. The ideal candidate combines strong PMO, data analytics and AI skills with excellent communication and stakeholder management capabilities. The role will be responsible for providing management with accurate insights on project performance, identifying risks and trends, improving PMO processes, and leveraging AI and automation to increase efficiency and decision-making quality.</p><p>&nbsp;</p><p><b>What you will do</b></p><ul><li>Support project planning, tracking, reporting, and governance across the project portfolio.</li><li>Maintain project plans, milestones, action trackers, and portfolio dashboards.</li><li>Monitor project progress against scope, schedule, budget, resources, and KPIs.</li><li>Prepare regular management and executive-level project status reports.</li><li>Support governance meetings, steering committees, and portfolio reviews.</li><li>Follow up on key actions, risks, issues, and dependencies to ensure timely resolution.</li><li>Ensure projects comply with PMO standards, processes, and reporting requirements.</li><li>Analyze project and portfolio data to identify trends, risks, performance gaps, and improvement opportunities.</li><li>Develop and maintain Power BI / Excel dashboards and management reports.</li><li>Create meaningful KPIs and metrics to measure project and portfolio performance.</li><li>Provide data-driven insights and recommendations to management.</li><li>Perform forecasting and scenario analysis related to project timelines, resources, costs, and delivery performance.</li><li>Improve the quality, consistency, and automation of PMO reporting.</li><li>Identify opportunities to use AI and automation to improve PMO processes and productivity.</li><li>Use AI tools to support project reporting, data analysis, meeting summaries, risk identification, and documentation.</li><li>Explore and implement AI-enabled solutions for project forecasting, issue/risk analysis, and management insights.</li><li>Develop practical use cases for generative AI within the PMO.</li><li>Automate repetitive reporting and data-management activities where possible.</li><li>Stay current with emerging AI tools, capabilities, and best practices relevant to project management.</li><li>Identify inefficiencies in existing PMO processes and recommend improvements.</li><li>Develop templates, workflows, dashboards, and standardized reporting mechanisms.</li><li>Support PMO maturity and continuous-improvement initiatives.</li><li>Help establish data-driven and technology-enabled ways of working across the PMO.</li></ul><p><br></p> </div><h2 class="h5">Skills</h2> <div data-jb-field="skills"><p><b>Required Skills to be successful</b></p><ul><li>Analytical &amp; Data-Driven Mindset</li><li>Project &amp; Portfolio Management</li><li>Business Acumen and Problem Solving</li><li>Process Improvement Stakeholder Management</li><li>Good Communication, Presentation and Attention to Detail</li><li>Proactive &amp; Results-Oriented Approach.</li></ul><p>&nbsp;</p><p><b>What equips you for the role</b></p><ul><li>Bachelor’s degree in Business, Engineering, Finance, Information Technology, Data Analytics, or a related field.</li><li>3–7 years of experience in PMO, project management, business analysis, portfolio management, or a similar role.</li><li>Strong experience with project reporting, governance, and performance tracking.</li><li>Advanced Excel skills and experience with Power BI or similar analytics/reporting tools.</li><li>PMP, PRINCE2, PMI-PMOCP, or other project management certification.</li><li>Experience with Power Automate, SQL, Python, or other automation/data tools.</li><li>Experience implementing AI or automation solutions in a business environment.</li><li>Experience working with project portfolio management or enterprise transformation programs.</li><li>Knowledge of Agile, Scrum, or hybrid project management methodologies.</li></ul><p>&nbsp;</p></div>

<p>Job Description – DevSecOps Engineer</p><p>Position</p><p><strong>DevSecOps Engineer</strong></p><p>Experience</p><p><strong>4–8 Years</strong></p><p>Location</p><p><strong>UAE – Dubai / Abu Dhabi</strong></p><p>Employment Type</p><p>Full-Time / Contract</p><p>Work Mode</p><p>Onsite / Hybrid – As per client requirement</p><p>Role Overview</p><p>We are looking for an experienced <strong>DevSecOps Engineer</strong> to integrate security practices throughout the software development and deployment lifecycle. The candidate will be responsible for building secure CI/CD pipelines, automating security controls, managing cloud infrastructure, and implementing security best practices across application and infrastructure environments.</p><p>The ideal candidate should have strong hands-on experience with <strong>DevOps, Cloud, Kubernetes, CI/CD, Infrastructure as Code, and application security</strong>, with the ability to embed security into automated development and deployment processes.</p><p>Key Responsibilities</p><ul><li><p>Design, implement, and maintain secure <strong>CI/CD pipelines</strong>.</p></li><li><p>Integrate security controls and automated security testing into the software development lifecycle.</p></li><li><p>Implement <strong>DevSecOps practices</strong> across development, testing, deployment, and production environments.</p></li><li><p>Automate infrastructure provisioning, configuration, security controls, and compliance checks.</p></li><li><p>Manage and secure cloud infrastructure across <strong>AWS, Azure, or GCP</strong>.</p></li><li><p>Implement and manage <strong>Infrastructure as Code (IaC)</strong> using Terraform, CloudFormation, or equivalent tools.</p></li><li><p>Deploy and manage containerized applications using <strong>Docker and Kubernetes</strong>.</p></li><li><p>Implement container and Kubernetes security controls.</p></li><li><p>Integrate SAST, DAST, SCA, secrets scanning, vulnerability scanning, and other security tools into CI/CD pipelines.</p></li><li><p>Monitor infrastructure and applications for security vulnerabilities and misconfigurations.</p></li><li><p>Work with development teams to identify and remediate security issues early in the development lifecycle.</p></li><li><p>Implement secure authentication, authorization, secrets management, and encryption mechanisms.</p></li><li><p>Support vulnerability management and security remediation activities.</p></li><li><p>Automate security monitoring, reporting, and compliance processes.</p></li><li><p>Participate in incident response and security investigations when required.</p></li><li><p>Ensure compliance with organizational security policies and applicable industry standards.</p></li><li><p>Collaborate with Developers, Cloud Engineers, Security Teams, Architects, and DevOps teams.</p></li><li><p>Continuously evaluate emerging DevSecOps tools, technologies, and security practices.</p></li></ul><p>Mandatory Skills</p><ul><li><p><strong>4–8 years of experience in DevOps / DevSecOps / Cloud Engineering.</strong></p></li><li><p>Strong experience with <strong>CI/CD pipelines</strong>.</p></li><li><p>Hands-on experience with <strong>Jenkins, GitLab CI, GitHub Actions, Azure DevOps</strong>, or equivalent.</p></li><li><p>Strong experience with <strong>Docker and Kubernetes</strong>.</p></li><li><p>Experience with <strong>Terraform / Infrastructure as Code</strong>.</p></li><li><p>Strong knowledge of <strong>AWS, Azure, or GCP</strong>.</p></li><li><p>Experience integrating security tools into CI/CD pipelines.</p></li><li><p>Knowledge of <strong>SAST, DAST, SCA, vulnerability scanning, and secrets management</strong>.</p></li><li><p>Strong understanding of Linux/Unix environments.</p></li><li><p>Good knowledge of networking and cloud security concepts.</p></li><li><p>Experience with Git and source-code management platforms.</p></li><li><p>Scripting/programming experience using <strong>Python, Bash, or PowerShell</strong>.</p></li><li><p>Understanding of secure software development and <strong>DevSecOps lifecycle practices</strong>.</p></li></ul><p>Security Tools – Preferred</p><br><p><strong>Desired Candidate Profile</strong></p><p>Experience with one or more:</p><ul><li><p>SonarQube</p></li><li><p>Checkmarx</p></li><li><p>Veracode</p></li><li><p>Snyk</p></li><li><p>Trivy</p></li><li><p>Aqua Security</p></li><li><p>Fortify</p></li><li><p>OWASP ZAP</p></li><li><p>HashiCorp Vault</p></li><li><p>CyberArk</p></li><li><p>Microsoft Defender for Cloud</p></li><li><p>Prisma Cloud</p></li></ul><p>Cloud & DevOps Technologies</p><p>Azure</p><ul><li><p>Azure DevOps</p></li><li><p>Azure Kubernetes Service (AKS)</p></li><li><p>Microsoft Defender for Cloud</p></li><li><p>Azure Key Vault</p></li><li><p>Azure Container Registry</p></li></ul><p>AWS</p><ul><li><p>AWS CodePi</p></li></ul>

<p>Job Description – Blockchain / Digital Assets Engineer</p><p>Position</p><p><strong>Blockchain / Digital Assets Engineer</strong></p><p>Experience</p><p><strong>4–8 Years</strong></p><p>Location</p><p><strong>UAE – Dubai / Abu Dhabi</strong></p><p>Employment Type</p><p>Full-Time / Contract</p><p>Work Mode</p><p>Onsite / Hybrid – As per client requirement</p><p>Role Overview</p><p>We are looking for an experienced <strong>Blockchain / Digital Assets Engineer</strong> to design, develop, integrate, and maintain blockchain-based applications and digital-asset platforms.</p><p>The ideal candidate should have strong hands-on experience with <strong>Blockchain, Ethereum/EVM, Solidity, smart contracts, Web3 technologies, APIs, wallets, and decentralized applications</strong>. Experience in financial services, digital assets, tokenization, custody, exchanges, or payment platforms will be highly preferred.</p><p>Key Responsibilities</p><ul><li><p>Design and develop scalable <strong>blockchain and digital-asset applications</strong>.</p></li><li><p>Develop, test, deploy, and maintain <strong>smart contracts</strong>.</p></li><li><p>Build and integrate blockchain applications with enterprise systems and financial platforms.</p></li><li><p>Develop secure and scalable <strong>Web3 APIs and backend services</strong>.</p></li><li><p>Integrate wallets, exchanges, custody platforms, blockchain nodes, and third-party services.</p></li><li><p>Develop decentralized applications (dApps) and blockchain-enabled enterprise solutions.</p></li><li><p>Implement tokenization solutions for digital assets and real-world assets.</p></li><li><p>Work with blockchain networks to read, write, and monitor on-chain transactions.</p></li><li><p>Develop transaction processing, validation, monitoring, and reconciliation capabilities.</p></li><li><p>Implement blockchain event listeners and real-time transaction monitoring.</p></li><li><p>Perform smart-contract testing, debugging, optimization, and deployment.</p></li><li><p>Analyze blockchain transactions and investigate transaction failures or anomalies.</p></li><li><p>Implement secure authentication, authorization, key management, and API integrations.</p></li><li><p>Collaborate with Product Managers, Architects, Security Teams, Compliance Teams, and business stakeholders.</p></li><li><p>Participate in architecture discussions, code reviews, testing, deployment, and production support.</p></li><li><p>Stay updated with developments in blockchain, tokenization, digital assets, Web3, and decentralized finance.</p></li></ul><p>Mandatory Skills</p><ul><li><p><strong>4–8 years of software development experience</strong>, with relevant Blockchain / Web3 experience.</p></li><li><p>Strong hands-on experience with <strong>Blockchain technologies</strong>.</p></li><li><p>Strong experience with <strong>Solidity and Smart Contract development</strong>.</p></li><li><p>Experience with <strong>Ethereum / EVM-compatible blockchain networks</strong>.</p></li><li><p>Strong understanding of blockchain architecture and transaction lifecycle.</p></li><li><p>Experience with Web3 libraries such as <strong>Web3.js, Ethers.js, or equivalent</strong>.</p></li><li><p>Experience developing and integrating <strong>REST APIs</strong>.</p></li><li><p>Strong programming experience in <strong>JavaScript / TypeScript, Python, or Java</strong>.</p></li><li><p>Experience with blockchain wallets and transaction signing.</p></li><li><p>Good understanding of cryptography, hashing, digital signatures, and public/private key concepts.</p></li><li><p>Strong knowledge of SQL and database technologies.</p></li><li><p>Experience with Git and modern software development practices.</p></li></ul><p>Blockchain Technologies</p><p>Experience with one or more:</p><ul><li><p>Ethereum</p></li><li><p>Polygon</p></li><li><p>Arbitrum</p></li><li><p>Optimism</p></li><li><p>BNB Chain</p></li><li><p>Solana</p></li><li><p>Hyperledger</p></li><li><p>Other EVM-compatible networks</p></li></ul><p>Smart Contract Development</p><br><p><strong>Desired Candidate Profile</strong></p><p>Strong understanding of:</p><ul><li><p>Solidity</p></li><li><p>ERC-20</p></li><li><p>ERC-721</p></li><li><p>ERC-1155</p></li><li><p>Smart-contract deployment</p></li><li><p>Contract upgrades</p></li><li><p>Gas optimization</p></li><li><p>Contract testing</p></li><li><p>Event handling</p></li><li><p>On-chain/off-chain integration</p></li></ul><p>Digital Assets – Preferred Domain Experience</p><p>Candidates with experience in one or more of the following will be preferred:</p><ul><li><p>Digital asset platforms</p></li><li><p>Cryptocurrency exchanges</p></li><li><p>Digital wallets</p></li><li><p>Institutional custody</p></li><li><p>Tokenization</p></li><li><p>Real-world asset (RWA) tokenization</p></li><li><p>Stablecoins</p></li><li><p>Digital securities</p></li><li><p>DeFi</p></li><li><p>Web3 applications</p></li><li><p>Blockchain-based payments</p></li><li><p>Asset management platforms</p></li><li><p>Trading platforms</p></li></ul><p>Blockchain Security</p><p>Strong understanding of:</p><ul><li><p>Smart contract security</p></li></ul>

<ul><li><p>Define and implement SLIs / SLOs and error budgets for business-critical digital banking services.</p></li><li><p>Build actionable observability (metrics, logs, traces, dashboards, and alerts) using Dynatrace, Prometheus, Grafana, and ELK, while reducing alert fatigue.</p></li><li><p>Leverage AI-driven insights and anomaly detection (Dynatrace Davis AI or equivalent AIOps platform) to proactively predict and resolve reliability issues before impact.</p></li><li><p>Lead incident management — from on-call triage and root-cause analysis to blameless postmortems with actionable follow-ups.</p></li><li><p>Improve deployment safety with robust rollout / rollback strategies, canary and blue-green deployments, and production readiness reviews.</p></li><li><p>Support and optimize microservices-based architectures, ensuring service reliability, scalability, and inter-service resilience.</p></li><li><p>Conduct capacity planning, performance tuning, and resilience testing, optimizing for both reliability and cost efficiency.</p></li><li><p>Automate operational toil — from runbooks and remediation scripts to proactive health checks and self-healing workflows.</p></li><li><p>Collaborate with DevOps to embed reliability gates and validations into CI / CD pipelines (GitHub Actions, Jenkins, GitLab CI / CD or Azure DevOps).</p></li><li><p>Own and evolve the observability and AIOps stack, driving intelligent automation and predictive alerting capabilities.</p></li><li><p>Maintain high-quality documentation, playbooks, and operational standards across environments.</p></li><li><p>Ensure operational compliance and security alignment with internal controls and regulatory standards.</p></li><li><p>Analyze system performance, availability, and cost data to continually optimize operations.</p></li><li><p>Provide reliability support and escalation guidance for critical production systems during major incidents.</p></li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li><br><ul><li><p>5+ years of experience in SRE or DevOps roles, building and managing large-scale, high-availability systems across banking, fintech, e-commerce, or other data-intensive digital ecosystems.</p></li><li><p>Bachelor’s degree in Computer Science or equivalent technical experience.</p></li><li><p>Strong experience with Linux environments and performance troubleshooting.</p></li><li><p>Proven expertise in Terraform and Infrastructure as Code (IaC) methodologies.</p></li><li><p>Proficiency with Kubernetes and container orchestration in microservices environments.</p></li><li><p>Hands-on experience with AWS (preferred); exposure to Azure or GCP is an advantage.</p></li><li><p>Deep knowledge of Dynatrace (AIOps, Davis AI), Prometheus, Grafana, and the ELK stack.</p></li><li><p>Experience implementing AI / ML-driven reliability or automation solutions (AIOps, anomaly detection, predictive alerting).</p></li><li><p>Practical understanding of CI / CD pipelines (GitHub Actions, Jenkins, GitLab CI / CD or Azure DevOps).</p></li><li><p>Experience with Kafka, RabbitMQ, Redis, Aurora, and RDS databases.</p></li><li><p>Strong scripting or programming skills in Python, Bash, or Go. The Ideal Candidate</p></li><li><p>Organized, structured, and meticulous in approach.</p></li><li><p>Experienced in cross-functional collaboration and working with distributed teams.</p></li><li><p>Strong analytical mindset with excellent troubleshooting skills for complex production systems.</p></li><li><p>Calm and composed communicator under pressure, capable of leading during high-impact incidents.</p></li><li><p>Proactive problem-solver who anticipates issues and drives preventive improvements.</p></li><li><p>Passionate about AI-driven automation, observability, and reliability engineering.</p></li><li><p>Continuously learning, keeping up-to-date with cloud-native, microservices, and SRE best practices.</p></li><li><p>A collaborative and adaptable team player who thrives in a fast-paced, regulated environment and is passionate about building reliable, scalable systems that empower digital banking innovation.</p></li></ul><p>Skills</p><p>SRE</p><p>Dynatrace</p><p>Kubernetes</p></li></ul>

<p>About the role<br><br>We operate a fleet of company-owned Android devices that run automated workflows: capturing notifications, reading on-screen state from apps and pushing structured events into our backend. We are looking for an engineer who lives inside the Android runtime rather than on top of it, and who can keep a large device fleet running reliably without babysitting.<br>This is not a standard app development role. There is no design handoff and very little UI work. The job is making Android do things it was not really built to do, at scale, and keeping it stable across OEMs and OS versions.<br><br>What you will own<br></p><ul><li><p>Build and maintain an AccessibilityService that traverses node trees across third-party apps and emits reliable, structured events</p></li><li><p>Build and maintain a NotificationListenerService that captures, parses and deduplicates notifications across apps</p></li><li><p>Write and maintain versioned selector maps so that a UI change in a target app degrades gracefully instead of breaking the fleet silently</p></li><li><p>Manage a fleet of 50 to 200 physical devices over ADB: provisioning, health checks, remote restarts, log collection, session recovery</p></li><li><p>Keep services alive under Doze, battery optimisation and aggressive OEM process killers (Xiaomi, Oppo, Vivo, Samsung)</p></li><li><p>Build the on-device data pipeline: local buffering, dedupe, idempotent delivery, retry, backpressure when the network is unavailable</p></li><li><p>Own observability: per-device heartbeats, capture success rates, alerting when a device silently stops reporting</p></li></ul><p><strong>Desired Candidate Profile</strong></p><p>Must have<br><br><strong>ADB and fleet operations</strong></p><ul><li><p>Deep command-line ADB: shell, uiautomator dump, input, dumpsys, logcat filtering, pm, am, ADB over TCP/IP</p></li><li><p>Experience running an ADB server against many devices at once, including the failure modes: offline devices, unauthorised states, USB hub flakiness, server crashes</p></li><li><p>scrcpy, Appium or UiAutomator2 in a real operational setting, not just a demo<br></p></li></ul><p><strong>AccessibilityService</strong></p><ul><li><p>Strong practical command of AccessibilityNodeInfo traversal, node recycling and stale-node handling</p></li><li><p>Knows which event types to subscribe to and why: TYPE_WINDOW_CONTENT_CHANGED, TYPE_WINDOW_STATE_CHANGED, TYPE_VIEW_SCROLLED, and how to avoid drowning in event volume</p></li><li><p>Has dealt with sparse or hostile node trees: Jetpack Compose semantics, WebView content, canvas-drawn UI, apps with FLAG_SECURE</p></li><li><p>dispatchGesture, focus handling and the limits of programmatic interaction on modern Android<br></p></li></ul><p><strong>NotificationListenerService</strong></p><ul><li><p>StatusBarNotification extras parsing, MessagingStyle, grouped and bundled notifications, RemoteViews fallback when extras are empty</p></li><li><p>Handling reposts, updates and cancellations without producing duplicate events<br></p></li></ul><p><strong>Platform</strong></p><ul><li><p>Kotlin, coroutines, foreground services, WorkManager, Room</p></li><li><p>Concrete knowledge of what changed and broke across Android 11 through 16: package visibility, foreground service types, notification permission, restricted settings for sideloaded apps</p></li><li><p>Comfortable with rooted and non-rooted device workflows, custom ROMs, and knowing when root is the wrong answer<br></p></li></ul><p><strong>Nice to have</strong></p><ul><li><p>Python or Node tooling around the ADB layer for orchestration</p></li><li><p>Frida, Xposed or LSPosed familiarity</p></li><li><p>Experience with MDM, kiosk mode or Android Enterprise device owner provisioning</p></li><li><p>Prior work on a device farm, QA automation lab or RPA product</p></li></ul>

<p>MLOps Engineer (Freelance) Location: Abu Dhabi, Dubai, Fujairah, UAE (Hybrid) Contract Duration: Initial 6-Month Contract with possibility of extension Employment Type: Freelance / Independent Contractor About the Role We are seeking an experienced MLOps Engineer to join our team on an initial 6-month freelance contract. This is a hybrid role offering a combination of onsite and remote work. The successful candidate will play a key role in building, automating, and maintaining the infrastructure and processes required to deploy, monitor, and scale machine learning solutions in production environments. This opportunity offers the potential for extension beyond the initial contract period, subject to project requirements and performance. Key Responsibilities Design, implement, and maintain scalable MLOps frameworks and automated machine learning workflows. Build and manage CI/CD pipelines for machine learning model development, testing, deployment, and monitoring. Collaborate closely with Data Scientists, Machine Learning Engineers, Data Engineers, and DevOps teams to operationalize AI solutions. Deploy, monitor, and manage machine learning models in production environments. Develop and maintain model versioning, governance, and monitoring processes. Automate model retraining, validation, and deployment workflows. Ensure reliability, scalability, security, and performance of machine learning infrastructure. Implement logging, monitoring, and alerting mechanisms for model and platform performance. Optimize cloud infrastructure and resource utilization for AI/ML workloads. Troubleshoot and resolve issues related to model deployment, infrastructure, and data pipelines. Promote MLOps best practices and contribute to continuous improvement initiatives.</p><p>Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field. 4+ years of experience in MLOps, DevOps, Machine Learning Engineering, or a similar role. Strong experience with Python and machine learning lifecycle management. Hands-on experience with MLOps platforms and tools such as MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, or Azure ML. Strong knowledge of CI/CD tools such as GitHub Actions, GitLab CI/CD, Jenkins, or Azure DevOps. Experience with containerization and orchestration technologies including Docker and Kubernetes. Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform. Understanding of infrastructure as code tools such as Terraform or CloudFormation. Experience with monitoring and observability tools. Strong knowledge of software engineering best practices, automation, and system reliability. Excellent analytical, troubleshooting, and communication skills. Preferred Qualifications Experience supporting Generative AI and Large Language Model (LLM) deployments. Familiarity with Databricks, Spark, and large-scale data processing platforms. Knowledge of Responsible AI, model governance, and compliance frameworks. Experience working in enterprise-scale production environments. Previous experience delivering projects within the UAE or GCC region. If you are passionate about building reliable and scalable machine learning platforms and enjoy working at the intersection of AI, cloud infrastructure, and automation, we would love to hear from you. Please note: This opportunity is open to freelancers/independent</p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>MLOps Engineer (Freelance)</p><p><br></p><p>Location: Abu Dhabi, Dubai, Fujairah, UAE (Hybrid)</p><p>Contract Duration: Initial 6-Month Contract with possibility of extension</p><p>Employment Type: Freelance / Independent Contractor</p><p><br></p><p>About the Role</p><p>We are seeking an experienced MLOps Engineer to join our team on an initial 6-month freelance contract. This is a hybrid role offering a combination of onsite and remote work.</p><p><br></p><p>The successful candidate will play a key role in building, automating, and maintaining the infrastructure and processes required to deploy, monitor, and scale machine learning solutions in production environments. This opportunity offers the potential for extension beyond the initial contract period, subject to project requirements and performance.</p><p><br></p><p>Key Responsibilities</p><ul><li>Design, implement, and maintain scalable MLOps frameworks and automated machine learning workflows.</li><li>Build and manage CI/CD pipelines for machine learning model development, testing, deployment, and monitoring.</li><li>Collaborate closely with Data Scientists, Machine Learning Engineers, Data Engineers, and DevOps teams to operationalize AI solutions.</li><li>Deploy, monitor, and manage machine learning models in production environments.</li><li>Develop and maintain model versioning, governance, and monitoring processes.</li><li>Automate model retraining, validation, and deployment workflows.</li><li>Ensure reliability, scalability, security, and performance of machine learning infrastructure.</li><li>Implement logging, monitoring, and alerting mechanisms for model and platform performance.</li><li>Optimize cloud infrastructure and resource utilization for AI/ML workloads.</li><li>Troubleshoot and resolve issues related to model deployment, infrastructure, and data pipelines.</li><li>Promote MLOps best practices and contribute to continuous improvement initiatives.</li></ul><p><br></p><p><br></p> </div><h2 class="h5">Skills</h2> <div data-jb-field="skills"><p>Required Skills &amp; Experience</p><ul><li>Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.</li><li>4+ years of experience in MLOps, DevOps, Machine Learning Engineering, or a similar role.</li><li>Strong experience with Python and machine learning lifecycle management.</li><li>Hands-on experience with MLOps platforms and tools such as MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, or Azure ML.</li><li>Strong knowledge of CI/CD tools such as GitHub Actions, GitLab CI/CD, Jenkins, or Azure DevOps.</li><li>Experience with containerization and orchestration technologies including Docker and Kubernetes.</li><li>Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.</li><li>Understanding of infrastructure as code tools such as Terraform or CloudFormation.</li><li>Experience with monitoring and observability tools.</li><li>Strong knowledge of software engineering best practices, automation, and system reliability.</li><li>Excellent analytical, troubleshooting, and communication skills.</li></ul><p><br></p><p>Preferred Qualifications</p><ul><li>Experience supporting Generative AI and Large Language Model (LLM) deployments.</li><li>Familiarity with Databricks, Spark, and large-scale data processing platforms.</li><li>Knowledge of Responsible AI, model governance, and compliance frameworks.</li><li>Experience working in enterprise-scale production environments.</li><li>Previous experience delivering projects within the UAE or GCC region.</li></ul><p><br></p><p>Apply Now</p><p>If you are passionate about building reliable and scalable machine learning platforms and enjoy working at the intersection of AI, cloud infrastructure, and automation, we would love to hear from you.</p><p>Please note: This opportunity is open to freelancers/independent contractors only and requires availability for a hybrid working arrangement in UAE.</p></div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Derq is an MIT spinoff building AI-powered traffic safety and smart infrastructure.<br> We’re a team of passionate innovators, leveraging the latest in AI and technology to transform the future of mobility.<br> Our platform enhances road safety and traffic management by turning real-time data into actionable insights for cities and road operators.<br> Our patented technology collects and analyzes data from connected sensors like cameras, radar, and traffic signal controllers to help predict and prevent road incidents.<br> We deploy edge and cloud solutions that make intersections and highways safer and smarter.<br> Role Overview We’re looking for a Senior Software Engineer to work on real-time systems powering traffic detection and smart mobility solutions while also contributing to web applications, APIs, and third-party integrations.<br> This role combines systems engineering and software development, with approximately 75% of the work focused on real-time edge and backend systems and 25% focused on application development, integrations, and operational tooling.<br> You'll work across Linux-based systems, cloud-connected services, internal tools, dashboards, and live traffic deployments where reliability, performance, and scalability are critical.<br> Key Responsibilities Design, develop, and maintain production-grade software systems across edge and cloud environments.<br> Build and optimize real-time data processing pipelines and system services supporting live traffic deployments.<br> Develop and maintain backend services, REST APIs, and integrations with third-party platforms and services.<br> Contribute to internal web applications, dashboards, and operational tools used for monitoring and managing deployed systems.<br> Integrate software with sensors, cameras, traffic controllers, and other edge devices.<br> Profile, debug, and optimize system performance across application, operating system, and networking layers.<br> Troubleshoot and resolve complex production issues in distributed and real-time environments.<br> Improve system observability through logging, monitoring, diagnostics, and performance tracking.<br> Build and maintain CI/CD pipelines, deployment workflows, and automation tooling.<br> Collaborate with ML, QA, deployment, and product teams to deliver robust, production-ready solutions.<br> 8+ years of experience in software engineering or a related field Strong experience with C++, Python, or both.<br> Solid Linux development experience.<br> Experience building, maintaining, or integrating backend services, REST APIs, and web applications.<br> Experience working with third-party APIs and software integrations.<br> Strong understanding of multithreading, concurrency, system performance, and production troubleshooting.<br> Working knowledge of networking fundamentals, including TCP/IP, DNS, routing, and secure connectivity.<br> Experience with Git, testing frameworks, and CI/CD practices.<br> Experience with cloud platforms, containerized applications, or distributed systems is a plus.<br> Exposure to edge computing, embedded Linux, hardware integration, sensors, or IoT systems is a plus.<br> Familiarity with frontend technologies, internal tooling, dashboards, or operational web applications is a plus.<br> Familiarity with computer vision pipelines or ML-powered systems is a plus.<br></span> </div>