Vp, AI Risk & Governance

VP, AI Risk & Governance role within Global Risk Management (GRM) responsible for maintaining and evolving MetLife’s AI risk and governance framework. Identifies and translates AI risks into governance requirements and practical controls, ensuring alignment with risk appetite, existing frameworks, and regulatory expectations. Collaborates across departments to shape AI risk management strategy, drive risk-based decisioning in AI approvals, and ensure consistency and scalability of governance for AI initiatives. Enables responsible AI development and innovation by balancing business value with risk oversight, issue escalation, and monitoring of AI risk themes and control effectiveness.

What you'd actually do

  1. Lead day-to-day execution of the AI governance approval process, including risk-based review, challenge, escalation, and alignment to enterprise risk appetite and responsible AI principles.
  2. Provide credible second-line challenge and thought leadership to senior stakeholders on acceptable use, control requirements, and mitigation strategies for AI risks.
  3. Translate risk appetite and regulatory expectations into actionable governance requirements and control expectations.
  4. Identify and assess novel, emerging, and cross-cutting risks arising from AI.
  5. Drive strategic improvements to financial and non-financial AI risk and governance processes, including transparency, efficiency, operating model design, and reporting.

Skills

Required

  • Risk management
  • AI technologies understanding
  • Machine learning
  • Generative AI
  • Agentic AI
  • Model risk
  • Data risk
  • Enterprise governance frameworks
  • Policies
  • Standards
  • Approval processes
  • Complex matrixed organizations
  • Stakeholder influence
  • Strategic thinking
  • Judgment
  • Problem-solving
  • Executive communication
  • Regulatory expectations
  • Responsible AI practices
  • Bachelor's degree

Nice to have

  • Advanced degree in data science, applied mathematics, AI/ML, actuarial science or a related field

What the JD emphasized

  • risk management experience within financial services or regulated industry
  • Deep understanding of AI technologies and associated risks, including machine learning, generative AI, agentic AI, model risk, and data risk
  • Proven experience designing, implementing, and enhancing enterprise governance frameworks, policies, standards, and approval processes.
  • Strong knowledge of regulatory, governance, and control expectations related to AI, models, data, and responsible AI practices.

Other signals

  • AI risk and governance framework
  • risk appetite
  • regulatory expectations
  • AI approval process
  • AI lifecycle controls