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<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>The Senior Business Intelligence Analyst will bring deep expertise in Power BI (or similar BI tools), advanced proficiency in SQL and Python, and a command of statistical analysis, along with the ability to translate complex healthcare data into strategic insights. This role requires someone who can work independently, mentor junior analysts, and partner closely with clinical, operational, and business leaders to drive data-informed decision-making.</p><br><br>Responsibilities:<br><ul><li><span>Leads the design, development, and maintenance of advanced dashboards and reports using Power BI (or Tableau/Looker/Qlik) to support clinical operations, quality, finance, and population health initiatives</span></li><li><span>Writes and optimizes complex SQL queries across large healthcare datasets (EHR/EMR, claims, clinical, operational data)</span></li><li><span>Analyzes healthcare-specific metrics such as patient outcomes, readmission rates, length of stay, utilization, cost-of-care, and quality measures (HEDIS, CMS Star Ratings, etc.)</span></li><li><span>Ensures compliance with healthcare data regulations (HIPAA, HITECH) and data governance best practices in all analyses and reporting</span></li><li><span>Partners with clinical, operations, finance, and executive leadership to define KPIs, identify data needs, and deliver actionable insights</span></li><li><span>Uses Python (Pandas, NumPy, SciPy, scikit-learn) for advanced data wrangling, automation, and predictive/statistical modeling</span></li><li><span>Applies advanced statistical techniques (hypothesis testing, regression, survival analysis, risk adjustment models, cohort analysis) to evaluate clinical outcomes, cost trends, and operational performance</span></li><li><span>Leads root-cause analysis on data quality issues, workflow inefficiencies, and performance gaps within clinical/operational processes</span></li><li><span>Mentors and provides technical guidance to junior/mid-level analysts on best practices in SQL, Python, and dashboard design</span></li><li><span>Drives automation of recurring reports and process improvements to enhance data pipeline efficiency</span></li><li><span>Collaborates with data engineering teams on data architecture, ETL pipelines, and data warehouse design as needed</span></li></ul><br>Qualifications:<br><ul><li><span>Bachelor's degree in data science, statistics, health informatics, computer science, or related field.</span></li><li><span>Advanced proficiency in Power BI or similar BI/visualization tools (Tableau, Looker, Qlik Sense), including DAX and data modeling&nbsp;</span></li><li><span>Expert-level SQL skills (complex joins, window functions, CTEs, query optimization, stored procedures)&nbsp;</span></li><li><span>Strong Python skills for data analysis and statistical modeling (Pandas, NumPy, SciPy, scikit-learn)&nbsp;</span></li><li><span>Advanced understanding of statistical methods (regression analysis, hypothesis testing, A/B testing, predictive modeling)&nbsp;</span></li><li><span>Familiarity with healthcare data standards and terminologies (ICD-10, CPT, HCPCS, HL7/FHIR) is highly desirable&nbsp;</span></li><li><span>Working knowledge of HIPAA and healthcare data privacy/compliance requirements&nbsp;</span></li><li><span>Proven ability to lead projects end-to-end and manage stakeholder relationships independently&nbsp;</span></li><li><span>Excellent communication and storytelling skills — able to translate technical/clinical data into insights for non-technical executives.</span></li><li><span>5+ years of experience as a Data Analyst, with significant experience in the healthcare industry (payer, provider, health system, or health-tech)&nbsp;</span></li><li><span>Experience with claims data, EHR/EMR systems (Epic, Cerner, etc.), or clinical data warehouses&nbsp;</span></li><li><span>Exposure to value-based care, population health management, or quality reporting programs (HEDIS, MIPS, Star Ratings)&nbsp;</span></li><li><span>Experience with cloud platforms (Azure, AWS, or GCP) and modern data warehousing (Fabric Snowflake, Redshift, BigQuery)&nbsp;</span></li><li><span>Familiarity with machine learning applications in healthcare (risk prediction, readmission models)&nbsp;</span></li><li><span>Experience with version control (Git) and Agile/Scrum methodologies&nbsp;</span></li><li><span>Prior experience mentoring or leading a small analytics team.</span></li></ul> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <strong><span><span><span><span><span><span><span>Senior Backend Engineer </span></span></span><span><span><span>(</span></span></span></span></span><span><span>Python /Node.js)</span></span></span></span></strong><p><span><span><span><span><span><span><span>Location: </span></span></span><span><span><span>Abu Dhabi, UAE</span></span></span></span></span></span><br><span><span><span><span><span><span>Employment Type: </span></span></span><span><span><span>Full-time&nbsp;</span></span></span></span></span></span></span></p><br><br><span><span><span><span><span><span>Job Summary</span></span></span></span></span></span><p><span>NorthBay is seeking a <strong>Senior Backend Engineer</strong> to architect and build scalable APIs and data processing pipelines powering <strong>AI-driven systems</strong>. The role involves integrating ML models into production workflows, managing data orchestration, and ensuring the overall <strong>reliability, security, and performance</strong> of AI services.</span></p><br><br><span><span><span><span><span><span>Key Responsibilities</span></span></span></span></span></span><ul><li><span>Design and develop scalable backend services using <strong>Python, Django, Flask, Node.js, and Nest.js</strong>.</span></li><li><span>Build and maintain scalable <strong>REST and GraphQL APIs</strong>.</span></li><li><span>Integrate <strong>machine learning inference endpoints, batch jobs, and model serving workflows</strong>.</span></li><li><span>Collaborate with DevOps and ML engineers to deploy models, manage <strong>feature stores</strong>, and handle large datasets.</span></li><li><span>Implement secure, high-performance backend systems with <strong>caching, queuing, and monitoring</strong>.</span></li><li><span>Partner with AI engineers to wrap ML models into APIs and deploy them into <strong>production environments</strong>.</span></li><li><span>Develop reusable, maintainable modules and implement <strong>unit and integration testing</strong>.</span></li><li><span>Support <strong>CI/CD pipelines</strong>, containerized deployments, and cloud-based backend infrastructure.</span></li></ul><p><span><span><span><span><span><span>Required Skills &amp; Qualifications</span></span></span></span></span></span></p><br><br><ul><li><span><strong>5+ years of professional backend development experience</strong>.</span></li><li><span>Strong hands-on experience with <strong>Python, Django, and Flask — mandatory</strong>.</span></li><li><span>Strong experience with <strong>Node.js and Nest.js</strong>.</span></li><li><span>Proficiency in <strong>TypeScript, REST/GraphQL APIs, PostgreSQL, and MongoDB</strong>.</span></li><li><span>Experience designing and implementing <strong>scalable and event-driven architectures</strong> using <strong>Kafka and/or RabbitMQ</strong>.</span></li><li><span>Hands-on experience with at least one major cloud platform: <strong>AWS or Azure</strong>.</span></li><li><span>Strong experience with <strong>Docker and Kubernetes</strong>.</span></li><li><span>Experience with <strong>API development, backend security, performance optimization, testing, and CI/CD</strong>.</span></li><li><span>Ability to work closely with <strong>AI/ML and DevOps teams</strong> to productionize AI solutions.</span></li></ul><p><span><span><span><span><span><span>Optional but Desirable (AI-Focused Skills)</span></span></span></span></span></span></p><br><br><ul><li><span>Experience integrating <strong>ML model serving frameworks</strong> such as <strong>FastAPI, Triton, or TorchServe</strong>.</span></li><li><span>Exposure to data pipeline and orchestration tools such as <strong>Airflow, Kubeflow, or Dagster</strong>.</span></li><li><span>Understanding of AI/ML observability tools such as <strong>Prometheus, EvidentlyAI, or Seldon Core</strong>.</span></li><li><span>Experience working with <strong>ML inference, model APIs, feature stores, or large-scale data processing</strong>.</span></li></ul> <br><br> </div>

The job holder is responsible for designing, building, and operating production-grade AI agents on Microsoft Foundry — LLM-powered systems that reason, use tools, and orchestrate multi-step workflows against enterprise data and services. This is a hands-on, pro-code role: the engineer writes Python, integrates Azure services, and ships agentic applications that drive measurable business impact. The engineer works within agile teams alongside Product, Data Science, and Architecture to take agent use cases from prototype to production.<br>Key Responsibilities:<br>AI Agent Development on Microsoft Foundry Design, build, and deploy pro-code AI agents on Microsoft Foundry, leveraging its agent framework, model catalogue, and tool/function-calling capabilities. Integrate agents with Palantir Foundry via MCP (Model Context Protocol) to fetch enterprise data and execute Ontology actions, alongside other tool, retrieval, memory, and multi-agent orchestration patterns in Python. Build evaluation harnesses and guardrails (groundedness, safety, cost, latency) and iterate on prompts, tools, and architectures based on measured outcomes. LLM Engineering & Productionization Apply prompt engineering, structured output, RAG, and grounding techniques appropriate to each use case. Operate agents in production: observability, tracing, cost monitoring, regression testing, and incident response. Manage versioning of prompts, tools, and agent configurations alongside code. Azure & Platform Integration Integrate with Azure services (Azure Open AI, AI Search, Storage, Functions, Container Apps, Key Vault, Entra ID) to deliver secure, scalable agent solutions. Build and maintain CI/CD pipelines for agent deployment, including automated evals as a release gate. Implement authentication, authorization, secret management, and data-handling patterns aligned with enterprise security standards. Cross-functional Collaboration Work closely with Product Managers, Data Scientists, and IT Architects to translate agent use cases into delivery plans. Communicate trade-offs (model choice, latency, cost, accuracy) clearly to technical and non-technical stakeholders. Champion agentic patterns and reusable components across the engineering organization.<br>Qualifications:Software engineering experience with hands-on production experience building LLM-based / agentic systems (tool use, orchestration, RAG, evals). Bachelor’s Degree in Computer Science, Engineering, or related quantitative field Advanced degrees preferred. Strong Python — idiomatic, typed, tested; comfortable with async and modern packaging Proven experience building production AI agents in code (e.g. Microsoft Foundry / Azure AI Foundry, Semantic Kernel, Auto Gen, Lang Graph, Llama Index, Open AI Agents SDK, or equivalent custom frameworks) Microsoft Foundry experience strongly preferred (agent authoring, model catalog, connectors, deployment) Azure exposure — Azure Open AI, AI Search, identity, storage, serverless compute; familiarity with Azure Dev Ops or Git Hub Actions Deep working knowledge of LLM application patterns: tool/function calling, structured outputs, RAG, memory, multi-agent orchestration Experience with evaluation frameworks and observability for LLM systems (tracing, prompt/response logging, automated evals) Dev Ops fundamentals: Git, CI/CD, containers, infrastructure-as-code; exposure to data engineering and vector stores is a plus High-energy, ownership-driven mindset Strong problem-solving and analytical skills Excellent communication and collaboration abilities Comfortable navigating ambiguity and driving clarity Experience in agile/start-up environments preferred Track record of taking AI/ML or agent projects from prototype to production

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Company Description<br><p>Ghobash Group capitalizes on opportunities within promising industry sectors by either acquiring existing companies or establishing new businesses. Aligned with the needs of a growing portfolio, the Group established Aban Investment to administer a host of centralized business functions (finance, legal, HR, marketing, etc.) all aimed at delivering greater cost efficiencies, value and best practices to each of its business units.</p><br><br>Job Description<br><p>The Azure Data Engineer is responsible for designing, implementing, and managing robust data solutions to meet business needs. This includes overseeing data pipelines, Azure data platform services, and delivering actionable insights through Power BI dashboards and reports. The specialist will play a critical role in transforming raw data into valuable insights, ensuring data accuracy, and supporting business intelligence initiatives across the organization.</p><br><ol><li><strong>Azure Data Platform Management:</strong> Design, implement, and manage Azure SQL databases, Azure Data Lake Storage, and related Azure &amp; Fabric services.</li><li><strong>ETL Processes and Data Pipelines:</strong> Create, monitor, and optimize ETL (Extract, Transform, Load) workflows to integrate data from multiple sources into centralized systems, ensuring reliability and performance.</li><li><strong>SQL and Python Development:</strong> Utilize SQL for querying, analysing, and managing relational databases, and develop Python scripts to automate data processes, integrate data sources, and support advanced analytics.</li><li><strong>Big Data and Advanced Analytics</strong>: Leverage Azure Databricks for big data processing, analytics, and machine learning workflows, and utilize tools like Apache Spark and Hadoop for processing large datasets.</li><li><strong>Data Warehousing:</strong> Develop and maintain enterprise data warehouses to support analytics and reporting needs while ensuring seamless integration with visualization tools.</li><li><strong>Data Security and Compliance</strong>: Implement robust data security measures to protect sensitive data, maintain compliance with organizational and regulatory standards, and support disaster recovery processes.</li><li><strong>Collaboration and Documentation</strong>: Collaborate with cross-functional teams to gather requirements and deliver data solutions while maintaining detailed documentation of data architectures, ETL processes, and Power BI standards.</li><li><strong>AI Enablement</strong>: Design, implement and Manage data solutions for the AI needs.</li></ol><p><strong>IT Policies and IT Processes impacted/addressed by this position:</strong></p><br><ol><li><strong>Database Management Process</strong>: Adherence to data governance processes and policies to ensure data accuracy and security.</li><li><strong>Data Security Policy</strong>: Ensuring compliance with data protection and security guidelines.</li><li><strong>Change Management Policy</strong>: Following procedures for managing changes in technology and processes.</li><li><strong>Business Continuity Policy</strong>: Supporting business continuity planning and disaster recovery processes.</li><li><strong>IT Incident Management</strong>: Participating in the resolution of IT incidents related to data solutions.</li></ol><br>Qualifications<br><ul><li><p>Bachelor’s degree in Computer Science, Information Technology, Business&nbsp;Administration, or a related field.</p><br></li><li><p>Advanced certifications in Azure Data Engineering, SQL, or Microsoft Power BI are preferred.</p><br></li></ul><br>Additional Information<br><p><strong>Experience:</strong></p><br><ul><li>Minimum of 7 years of experience in data engineering, data warehousing, ETL processes, and business intelligence development.</li><li>Proven expertise in Azure Data Factory, Azure Databricks, and Power BI development.</li><li>Strong experience in SQL for database management, querying, and optimization.</li><li>Any POC project for AI enablement for end users.</li><li>Demonstrated proficiency in Python for data automation, analytics, and advanced transformations.</li><li>Experience in managing data pipelines and integrating large data sets for analysis.</li><li>Demonstrated experience in collaborating with stakeholders and presenting data-driven insights.</li><li>Experience in building Data solutions for AI recipients that successfully helped the business with a tangible benefit.</li></ul><p><strong>Skills &amp; Abilities:</strong></p><br><ul><li>Proficient in Azure services: Data Factory, Databricks, Data Lake, SQL Database, and Synapse Analytics.</li><li>Advanced Power BI expertise, including DAX, data modelling, and report development.</li><li>Strong SQL and Python skills for data processing, analysis, and automation.</li><li>Experience with big data frameworks like Apache Spark and Hadoop.</li><li>Proficiency in relational databases: Microsoft SQL Server, MySQL, and PostgreSQL.</li><li>Excellent organizational, problem-solving, and communication skills.</li><li>Familiarity with data security and compliance standards.</li></ul><br><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> About the job Full Stack Developer (Angular &amp; Django) Senior Full Stack Developer (Angular &amp;&nbsp;Django) About Us <p>Our regional office, based in Dubai, manages the UAE market and collaborates closely with key global stakeholders.</p><br> <p>We operate in a lean and efficient organization with a flat management structure, enabling quick decision-making and direct communication with leadership.</p><br> Why Join Us? <ul><li>Work with important industry players and contribute to impactful projects.</li><li>Join a stable and well-established organization with a solid reputation.</li><li>Enjoy on-time payments and a professional, highly-skilled team culture.</li><li>Benefit from mutual knowledge sharing and skill development in a collaborative environment.</li><li>Experience minimal hierarchy and direct access to decision-makers.</li></ul> Role Description <p>As a Senior Full Stack Developer, you will:</p><br> <ul><li>Design, build, and maintain scalable applications with a focus on <strong>Angular</strong> for responsive, user-friendly, and accessible interfaces.</li><li>Develop efficient product data workflows, enabling users to validate and share product information.</li><li>Build and maintain <strong>Python/Django</strong> backend systems for data aggregation, transformation, and partner integrations (via APIs or dedicated pipelines).</li><li>Integrate with leading BI and enterprise platforms such as <strong>Snowflake, Salesforce, and Tableau</strong>.</li></ul> Candidate Profile <ul><li>English proficiency level <strong>B1</strong>, enabling effective communication and active participation in daily meetings, sprint planning, backlog refinement, sprint reviews, and discussions with Product Managers and the Tech Lead.</li><li>At least <strong>4 years</strong> of hands-on experience in full-stack development using <strong>Angular (TypeScript)</strong> and <strong>Python (Django)</strong>.</li><li>Proficiency in working with relational databases, particularly <strong>PostgreSQL</strong>.</li><li>Solid understanding of <strong>API-first architectures</strong> and integration best practices.</li><li>Strong analytical thinking for interpreting documentation and designing integrations.</li></ul> Bonus Skills <ul><li>Experience with <strong>Django REST Framework, FastAPI, Django Ninja, and Celery</strong> for background processing.</li><li>Advanced Angular experience, including:<ul><li>Reactive programming with <strong>RxJS, NgRx, or NGXS</strong>.</li><li>Building complex forms and state management architectures.</li></ul></li><li>Experience with <strong>MongoDB</strong> or other <strong>NoSQL</strong> databases.</li><li>Understanding of hybrid data architectures, where relational databases (<strong>PostgreSQL</strong>) are combined with NoSQL solutions (e.g., <strong>MongoDB</strong>) or <strong>PostgreSQL JSONB</strong> for flexible product data storage.</li></ul> What We Offer <ul><li>Work from office.</li><li>Competitive compensation, paid on time.</li><li>Additional paid leave depending on tenure.</li><li>A culture of shared growth and peer learning.</li></ul> <p>Apply now!</p><br> <br> <br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>Project description As the AI Engineer within the Data Analytics &amp; Artificial Intelligence division, you will design, develop, and deploy production-grade AI solutions using Microsoft Azure AI Services and Python. Your focus will be on advancing the bank's capabilities in Generative AI, Agentic AI, intelligent automation, knowledge search, and content summarization by building scalable, secure, reliable, and responsible AI systems that enhance operational efficiency, customer engagement, and decision intelligence across the Group. The AI Engineer will work closely with Data Scientists, Platform Engineers, DevOps/MLOps Engineers, Business Analysts, and product teams to deliver end-to-end AI solutions. The role is critical for driving the organization's digital transformation agenda, empowering business users with advanced AI-powered tools, and improving operational efficiency through intelligent automation using Banks GERNAS OS platform and Agent Development Kit (ADK). Responsibilities AI Solution Design &amp; Development: Design, build, and deploy AI-powered applications using Azure AI Services, including Azure OpenAI Service, Azure Machine Learning, Azure Cognitive Services (Speech, Vision, Language), Azure AI Search, Azure Functions, and Azure Databricks. LLM Integration &amp; Generative AI: Develop and integrate Large Language Model (LLM) solutions using Azure OpenAI endpoints (GPT-4.1, GPT-4o, GPT-4o-mini) routed through FAB's centralized AI Hub gateway for governance, observability, and capacity management. Build enterprise use cases such as knowledge search, document intelligence, content summarization, call analytics, sentiment analysis, and workflow automation. Python Engineering &amp; Backend Development: Write clean, modular, and production-grade Python code for AI/ML model development, API integrations, data processing pipelines, backend services, and automation workflows using frameworks such as LangChain, LlamaIndex, Semantic Kernel, LangGraph, and FastAPI. RAG &amp; Semantic Retrieval: Implement Retrieval-Augmented Generation (RAG) pipelines, embeddings, vector search, semantic retrieval architectures, prompt engineering, and evaluation techniques for enterprise knowledge mining and document intelligence. Agentic AI Development: Design and develop intelligent agentic AI systems capable of planning, reasoning, tool execution, and orchestration across enterprise systems using FAB's GERNAS OS platform and Agent Development Kit (ADK) in a secure and governed manner. Model Evaluation &amp; Responsible AI: Implement model evaluation metrics for accuracy, hallucination detection, bias, latency, and throughput in alignment with FAB's Responsible AI framework. Ensure AI solutions comply with FAB's security, data privacy, model governance, and regulatory requirements, including controls for accuracy, hallucination, bias, latency, and resilience. Deployment &amp; Production Operations: Deploy, monitor, and optimize AI solutions in production environments using CI/CD practices, containerization, observability, logging, performance monitoring, and cost optimization techniques. Collaboration &amp; Stakeholder Engagement: Collaborate with data scientists, platform engineers, DevOps/MLOps engineers, business analysts, and product teams to convert business requirements into scalable AI solutions. Innovation &amp; Continuous Learning: Continuously evaluate emerging Azure AI, Generative AI, and Agentic AI capabilities and recommend practical adoption opportunities aligned with FAB's AI strategy. Stay abreast of state-of-the-art developments in generative AI and agentic architectures Skills Must have Experience: total 6 to 10+ years in software field with minimum 3+ years of hands-on experience in designing, developing, and deploying AI/ML or Generative AI solutions in production environments. Minimum 3-4 yrs of working experience mandatory on below technical skills sets: Azure AI Services: Demonstrated working experience with Microsoft Azure AI Services including Azure OpenAI, Azure Machine Learning, Azure Cognitive Services, Azure AI Search, Azure Functions, and Azure Databricks. Python Programming: Strong proficiency in Python programming, including experience with REST APIs, SDKs, asynchronous processing, data manipulation, backend development, and AI application frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, FastAPI). LLM &amp; Generative AI: Deep understanding of machine learning, statistical modeling, NLP, generative AI principles, LLM application development, prompt engineering, RAG architecture, embeddings, vector databases, semantic search, and model evaluation techniques. ML Libraries &amp; Frameworks: Advanced proficiency in ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and NLP libraries (spaCy, NLTK). Vector Databases: Experience with vector databases including FAISS, Azure AI Search, ChromaDB, and Pinecone. DevOps/MLOps: Hands-on experience with DevOps/MLOps practices and tools such as Git, Docker, Kubernetes, CI/CD pipelines, MLflow, Terraform, Azure Monitor, and Application Insights. Cloud Security &amp; Integration: Understanding of cloud security, identity and access management, data privacy, encryption, logging, monitoring, and secure API integration patterns. AI Ethics &amp; Governance: Awareness of ethical considerations and responsible AI practices, including fairness, accountability, transparency, bias detection, hallucination mitigation, and compliance in AI systems. Nice to have NA Other Languages English: C2 Proficient Seniority Lead</p><br> </div>

<ul><li><p>The Backend Engineer is responsible for designing, developing, and maintaining scalable, secure, and high-performance backend systems that power AI-driven applications. This role plays a critical part in building robust APIs, integrating AI/ML services, and ensuring reliable data processing and system performance in production environments.</p></li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li><p>Bachelor’s degree in Computer Science, Engineering, or a related field.</p></li><li><p>7+ years of experience in backend development.</p></li><li><p>Strong programming expertise in Python, Java, Node.js, etc.</p></li><li><p>Proven experience building scalable APIs and microservices architectures.</p></li><li><p>Strong knowledge of databases (SQL and NoSQL) such as PostgreSQL, MySQL, MongoDB, or Cosmos DB.</p></li><li><p>Experience with cloud platforms (Azure, AWS, or GCP).</p></li><li><p>Solid understanding of distributed systems, caching, and asynchronous processing.</p></li><li><p>Experience with Git and version control workflows.</p></li><li><p>Strong debugging and problem-solving skills.</p></li></ul>