Product Manager, Sensitive Deployments

OpenAI OpenAI · AI Frontier · San Francisco, CA · Product Management

Product Manager for Integrity team focusing on sensitive AI deployments, including government, regulated enterprise, privacy-constrained environments, and agentic workflows. The role involves defining product strategy, measuring risk, building agentic investigation workflows, and creating launch playbooks for high-risk domains.

What you'd actually do

  1. Own the roadmap for sensitive deployment Integrity controls and readiness criteria.
  2. Define how we measure residual risk, decision quality, review quality, and mitigation effectiveness.
  3. Build agentic investigation and context-assembly workflows for complex, multi-step misuse patterns.
  4. Partner with Policy, Legal, Privacy, Safety Systems, User Ops, Government, and product teams to build shared capabilities.
  5. Create launch and deployment playbooks for sensitive customer, capability, and product contexts.

Skills

Required

  • Product management
  • AI
  • Integrity
  • Trust and Safety
  • Security
  • Privacy
  • Risk Management
  • Government
  • Regulated Enterprise
  • AI Safety
  • Policy interpretation
  • Threat modeling
  • Product requirements definition
  • Metrics definition
  • Operational workflows
  • Tradeoff frameworks
  • Agentic AI systems
  • Platform development
  • Launch strategy
  • Deployment strategy

Nice to have

  • Experience with sensitive deployments
  • Experience with government or high-stakes deployments
  • Experience with regulated or high-trust enterprise contexts
  • Experience with zero data retention and privacy-constrained environments
  • Experience with agentic workflows

What the JD emphasized

  • shipped complex product systems in AI, integrity, trust and safety, security, privacy, risk, government, regulated enterprise, or AI safety
  • agentic AI products
  • build the platform layer that makes them safer to deploy

Other signals

  • sensitive deployments
  • government and high stakes deployments
  • regulated or high-trust enterprise contexts
  • zero data retention and privacy-constrained environments
  • agentic workflows