Description :

Key Responsibilities :

Copilot & Fabric Agent Engineering :

- Design, configure, and deploy Copilot experiences and Fabric Agents across Lakehouse, Warehouse, and Power BI semantic models.

- Define agent instructions, system prompts, and grounding strategies aligned to business use cases.

- Implement guardrails to control data scope, tone, response format, and behavior.

- Tune Copilot interactions to improve accuracy, explainability, and relevance.

Python & AI Orchestration :

a. Use Python to :

- Orchestrate AI workflows in Fabric notebooks.

- Pre-process and enrich data for AI consumption.

- Validate Copilot outputs programmatically.

- Automate testing and evaluation of agent responses.

- Implement Python-based evaluation frameworks (accuracy, relevance, hallucination detection).

- Integrate Python logic with Fabric APIs and metadata layers.

- Microsoft Fabric Expertise

Work closely with Data Engineers to :

- Optimize Lakehouse and Warehouse structures for Copilot consumption.

- Ensure data is curated, well-modeled, and semantically rich.

Leverage Fabric components :

- OneLake.

- Notebooks (PySpark / Python).

- Data Pipelines.

- Power BI Semantic Models.

- Ensure Copilot interactions respect Row-Level Security (RLS) and role-based access control (RBAC).

- Copilot Prompt & Experience Design

- Design and test :

- System prompts.

- Few-shot examples.

- Structured response templates.

- Reduce hallucinations through :

- Strong grounding in Fabric datasets.

- Explicit constraints and validation logic.

Optimize Copilot for :

- Natural language Q&A.

- Insight summaries.

- Trend explanations.

- Root-cause analysis narratives.

- Responsible AI & Governance

- Apply Responsible AI principles :

- Transparency.

- Reliability.

- Data privacy.

- Define usage boundaries and acceptable output guidelines.

- Partner with Security and Compliance teams to :

- Validate data exposure.

- Ensure Copilot aligns with enterprise policies.

- Testing, Validation & Iteration

- Conduct structured testing with business users.

- Capture feedback and refine prompts and agents.

Measure :

- Accuracy.

- Time-to-insight.

- User satisfaction.

- Document limitations, risks, and best practices.

- Documentation & Knowledge Transfer

- Produce clear documentation for :

- Copilot configurations.

- Prompt strategies.

- Known limitations.

- Support handover to production or scale-out teams.

- Contribute to internal AI and Fabric standards.

Required Technical Skills :

Core Skills (Must-Have) :

- Strong Python development (advanced).

- Data processing.

- Automation.

- AI evaluation logic.

- Microsoft Fabric (hands-on).

- Notebooks (Python / PySpark).

- Lakehouse / Warehouse.

- OneLake.

- Copilot & Fabric Agents

- Prompt engineering.

- Agent configuration.

- Copilot experience tuning.

- Power BI Semantic Models

- Understanding of how Copilot consumes metadata.

- SQL & Data Modeling

- Star schema concepts.

- Analytical data structures.

AI & GenAI Skills :

- Applied Generative AI concepts.

- Prompt engineering and prompt chaining.

- LLM behavior tuning and evaluation.

- Grounding and context injection strategies.

- Hallucination mitigation techniques.

Nice-to-Have Skills :

- Azure OpenAI integration experience.

- Experience with evaluation frameworks (e.g. , custom scoring, LLM-as-judge).

- Experience deploying AI solutions in regulated environments.

- Familiarity with Power Platform or Teams Copilot integration.

Experience Requirements :

- 5+ years in data, analytics, or AI engineering.

- 2+ years applying Generative AI in production or POC environments.

- Proven experience with Microsoft Fabric and Copilot.

- Strong background in Python-driven analytics or AI workflows.