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)