AI Governance Lead

Insight Global is looking for an AI Governance Lead for one of our financial services clients. This person will serve as a strategic and hands-on partner to the AI leadership team, helping shape how the organization implements, governs, and scales AI-specifically within the Microsoft Copilot and M365 ecosystem. This could involve building and maintaining Copilot Studio agents, designing grounding and guardrail patterns, and partnering with business users to translate real workflows into AI-enabled solutions. This person will help to develop and operationalize AI governance standards including acceptable use, human-in-the-loop controls, documentation expectations, and risk classification models aligned to enterprise compliance requirements. Other possibilities include: creating and curating a centralized prompt library, establishing metadata standards, and defining when and how prompts should be used across the organization. Additionally, this person may host office hours, demos, and community enablement sessions to help users adopt best practices and scale responsibly. They will collaborate closely with risk, compliance, data protection, and platform engineering teams to ensure AI solutions remain safe, governed, auditable, and aligned to enterprise policies. This is a highly execution-focused role-requiring someone who can prototype, test, validate, document, and continuously improve AI agents, prompts, and governance artifacts in an evolving environment.

Deep, hands-on experience with Microsoft Copilot, Copilot Studio, and the M365 ecosystem (SharePoint, Teams, OneDrive, Entra, Purview, Power Platform)

Experience designing and implementing AI governance frameworks (acceptable use, human-in-the-loop controls, documentation standards, auditability)

Demonstrated ability to build, deploy, and maintain agentic AI solutions (intent design, grounding, guardrails, lifecycle/version management)

Strong command of prompt engineering best practices, including structured prompts, reproducibility, grounding, and validation

Experience creating and managing a prompt library with metadata and usage guidance

Ability to translate business workflows into scalable, governed AI-enabled solutions

Comfort working in ambiguous, early-stage environments; ability to create lightweight standards and iterate

Excellent communication skills and ability to build and support user communities

Familiarity with data protection, privacy, and information classification concepts, especially as they apply to AI solutions

Strong execution mindset - able to build, test, document, and refine solutions (not just high-level advising) Experience in financial services or other regulated environments

Background working with enterprise risk, compliance, or audit partners

Experience with LLMOps, AI assurance, or evaluation frameworks

Prior work enabling large user communities (playbooks, office hours, training, adoption strategy)