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Data Engineer -Azure Foundry

Summary

Build and deploy AI agents and copilots using Microsoft AI Foundry and Fabric, integrating RAG patterns with enterprise data to accelerate AI use cases for a logistics-focused enterprise.

Dubai, United Arab Emirates | Posted on 05/12/2026

Accelerate the adoption of Microsoft AI Foundry across Bahriby rapidly converting approved demand and enterprise architecture (EA) blueprint opportunities into working, value-driven AI use cases.

The role acts as a hands‑on bridge between Enterprise Architecture, Data & Analytics and business demand, delivering practical AI solutions using Microsoft Fabric, Azure AI Foundry and existing Bahri data assets, while enabling sustainable in‑house capability.

Key Responsibilities

Use Case Acceleration & Delivery

  • Rapidly design and implement AI use cases sourced from:
    • The approved demand intake channel
    • Translate high‑level business problems into deployable AI Foundry solutions (MVP to pilot to scale)

Microsoft AI Foundry & Fabric Enablement

  • Build and deploy AI applications using Microsoft AI Foundry, including:
    • Agents, copilots, and AI workflows
    • Model catalog and Azure OpenAI models
    • Develop Retrieval‑Augmented Generation (RAG) patterns grounded in:
      • OneLake / Microsoft Fabric
      • SharePoint and enterprise data sources
  • Implement fit‑for‑purpose ML and analytics models (forecasting, classification, anomaly detection) using Azure ML and/or Fabric
  • Integrate analytical outputs into AI agents and business workflows
  • Work closely with:
    • Enterprise Architecture to ensure alignment with target‑state architectures
    • Data teams to reuse certified datasets, semantic models, and pipelines
  • Follow EA guardrails while prioritizing speed and reuse over bespoke solutions
  • Apply pragmatic MLOps and AI governance practices aligned with Bahri standards
  • Evaluate AI solutions using AI Foundry evaluation tools (groundedness, relevance, safety)
  • Ensure documentation of:
    • Use case objectives
    • Deployment approach and limitations
  • Work alongside BI analysts, data engineers, and product owners
  • Enable internal teams by sharing reusable patterns, templates, and reference implementations

Requirements

Required Qualifications

  • Strong Python skills for data analysis and AI development
  • Hands‑on experience with Microsoft Azure AI services, preferably:
    • Microsoft Fabric
  • Experience building RAG‑based applications
  • Solid understanding of analytics, data modeling, and applied machine learning
  • Ability to operate in ambiguous environments and deliver rapidly

Preferred Qualifications

  • Prior experience accelerating AI or analytics use cases in large enterprises
  • Familiarity with EA or target architecture models
  • Experience with Dataiku DSS (nice‑to‑have, not mandatory)
  • Exposure to agent frameworks (Semantic Kernel, LangChain)
  • Experience in logistics, shipping, or asset‑intensive industries
  • Azure AI Engineer certification (preferred, not essential)

See also

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