Jobs / United States / OpenAI UK Ltd
Program Manager, Government Trusted Access
OpenAI UK Ltd · 🇺🇸 Washington, DC
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- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
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Sponsor Radar — OpenAI UK Ltd
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About the role
About the Team OpenAI for Government works with U.S. and allied government institutions to support the responsible adoption of AI across defense, intelligence, federal civilian, state and local, and international public-sector missions. We help public servants use frontier AI in ways that are effective, trusted, and grounded in real-world requirements for safety, reliability, security, compliance, and accountability. Government Trusted Access programs help eligible public-sector organizations and practitioners use advanced capabilities for approved, high-value work in sensitive domains. These programs bring together OpenAI for Government, Product Policy, Legal, Security, International, Research, User Operations, Technical Success, Global Affairs, and domain experts. Each program has distinct eligibility criteria, safeguards, and decision owners; our job is to make the overall government experience coherent and executable. About the Role We are seeking a Program Manager to coordinate OpenAI’s Government Trusted Access portfolio across high-trust domains, such as cyber and bio. You will build and run the operating mechanisms that move government participants from initial interest through review, onboarding, activation, ongoing support, and program improvement. The right person is a highly organized, low-ego operator who can move between strategy and detail. You are comfortable working across technical, policy, legal, safety, security, customer, and operational teams; you build durable systems without adding unnecessary process; and you communicate clearly when facts, ownership, or requirements are still evolving. This role is based in Washington, DC. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: - Coordinate government participation across domain-specific Trusted Access programs, including cyber and biology, while helping stand up future programs as the portfolio evolves. - Own the end-to-end program operating rhythm across intake, qualification, review, approval, onboarding, activation, ongoing support, renewal, and offboarding. - Maintain a clear portfolio view of applicants and participating organizations, access levels, requirements, owners, dependencies, commitments, risks, and decisions needed. - Build practical program mechanisms such as roadmaps, ownership maps, decision logs, risk registers, service standards, operating reviews, dashboards, and executive updates. - Coordinate cross-functional reviews across OpenAI for Government, Safety, Product Policy, Legal, Security, Product, Research, User Operations, Technical Success, Global Affairs, and domain experts. - Preserve clear decision boundaries: ensure the right domain owner makes eligibility, policy, safety, security, and access decisions while keeping the broader process moving. - Identify stalled reviews, broken handoffs, unclear ownership, capacity constraints, and recurring operational gaps; bring the right context, options, and recommendation to resolve them. - Partner with government-facing teams to set accurate expectations, coordinate participant communications, and ensure commitments are tracked through completion. - Define and monitor program health through measures such as review time, backlog age, onboarding completion, activation, support demand, participant outcomes, and operational risk. - Turn manual and one-off work into scalable workflows, documentation, training, automation, and tooling while retaining appropriate human judgment for sensitive decisions. - Capture lessons across domains and translate them into reusable operating patterns without flattening meaningful differences between programs. You might thrive in this r