Copilot

Key Responsibilities

• Opportunity Identification: Audit IT support workflows to identify high-ROI automation candidates.
• Agent Development:
  • Design and build intelligent, conversational agents using Copilot Studio Agent Builder .
  • Develop complex, orchestrated agentic workflows using the Microsoft Agent Framework (MAF) .
• Validation & Quality Assurance:
  • Implement rigorous validation protocols (e.g., adversarial testing, prompt rubrics, and RAG retrieval evaluation) to ensure AI outputs align with business rules and compliance requirements.
  • Maintain "human-in-the-loop" oversight mechanisms and monitor for drift (data, prompt, and output) to ensure ongoing accuracy.
• Cost Management & FinOps:
  • Analyze and optimize Total Cost of Ownership (TCO) , including API consumption, token usage, infrastructure overhead, and maintenance costs.
  • Build "value-versus-spend" models to justify AI investments and identify opportunities for rightsizing/deprovisioning inefficient agents.
• Framework & Risk Alignment: Ensure all developments satisfy Shell framework standards and IRA guidelines regarding data privacy, security, and ethical AI.
• Productionization: Monitor performance via telemetry and establish continuous feedback loops for iterative improvements.

Technical Requirements

• Core Platforms: Proven experience with Copilot Studio and Microsoft Agent Framework (MAF) .
• Validation Tooling: Experience with AI evaluation frameworks (e.g., Promptfoo, Ragas) or automated testing suites for LLM outputs.
• Microsoft Stack: Strong proficiency in Power Platform, Azure AI Services, and associated M365 governance.
• Financial/Analytical Skills: Ability to perform cost-benefit analysis, track consumption metrics, and translate technical usage into business ROI.
• Governance & Security: Familiarity with implementing enterprise-grade security within Microsoft environments.

Soft Skills

• Analytical Mindset: Ability to translate complex business problems into modular technical requirements.
• Governance-First Approach: Eagerness to balance rapid innovation with the rigor required by internal risk and assurance policies.
• Financial Fluency: Ability to articulate the cost drivers of AI to stakeholders and manage project budgets effectively.