OpenAI

OpenAI

Product Manager, Codex Security Controls & Partner Interfaces

Remote - US · Contract

Sponsorship not specifiedDetected 8 days ago
CI/CDOAuthAgentic AICybersecuritySIEMResearch

About the role

  • This role focuses on securing Codex itself: how identity, permissions, tools, MCP servers, repositories, secrets, networks, and high-impact actions are governed across Codex products.
  • OpenAI's Cyber team works to make frontier AI safe, trusted, and transformative for developers and enterprises.
  • Our goal is to make Codex secure by default, governable by enterprises, and interoperable with the security products customers already trust.

Responsibilities

  • Have experience building integrations across complex enterprise systems or partner ecosystems.
  • Communicate credibly with developers, security architects, CISOs, researchers, and partner product teams.
  • Build native security controls for Codex

Nice to have

  • Experience in application security, identity, cloud security, data security, source control, CI/CD, SIEM, or enterprise governance.
  • Familiarity with RBAC, ABAC, policy-as-code, OAuth, OIDC, workload identity, or secrets management.
  • Experience with AI agents, MCP, sandboxed execution, prompt-injection defenses, or agent-security evaluations.
  • During your first six months, you will have helped establish:
  • A common architecture for security context, policy decisions, inspection, telemetry, and response.
  • Evaluation and launch criteria for high-risk Codex capabilities.
  • We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products.
  • For additional information, please see OpenAI's Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf.

Skills

  • how identity, permissions, tools, MCP servers, repositories, secrets, networks, and high-impact actions are governed across Codex products.

This listing is sourced directly from OpenAI's careers page and normalized into a canonical job model.