Sr. AI Governance Manager

Required Skills

• Strong technical foundation with a deep understanding of AI.
• Responsible AI governance knowledge is preferred; ethics and process can be learned.
• Strategic mindset with operational execution capabilities.
• Effective communicator who can educate and influence teams across the organization.

Day-to-Day Responsibilities

• Own all MGS AI use cases and collaborate across all business segments.
• Run the impact assessment process for every AI use case.
• All use cases must go through this team via a defined intake process.
• Each segment has its own contact who also assesses use cases.
• Conduct audits and ensure teams (use case owners, data analytics) understand governance.
• Help identify and mitigate risks.
• Navigate leadership teams and present governance processes.
• Participate in roadshows to promote AI governance across the company.
• Responsible for ensuring ~150K employees understand the AI process.

Strategic Focus

• Evolving governance model based on Responsible AI frameworks (e.g., RAI governance from effem.com).
• Five main phases: pre-assessment, impact, etc.
• The process is continuously evolving.
• Expansion from GenAI to broader AI domains, including genetic AI.
• Lower-risk use cases may be governed by individual segments.

Business & Technical Context

• Business breadth is crucial.
• Must understand where use cases originate and be empowered to say no.
• Needs to be senior and capable of making tough decisions.
• Tech stack: Primarily Azure/Microsoft.
• Some teams are shifting toward Google (e.g., snacking).
• Kellanova acquisition brings AWS into the mix.
• Fast-paced, dynamic environment.
• Tooling and architecture: Governance tools are essential.
• Use cases span multiple layers:
• Middleware (possibly Max Teams).
• Build/buy/existing SaaS vendors.
• Platforms like SAP with add-on widgets that require assessment.
• Must understand both platform architecture and how AI integrates across layers.

This is a high PRIORITY requisition.