The Frontier Assurance team brings independent scrutiny into OpenAI’s safety decisions and helps the public understand and assess our safety work. We lead third-party assessments and safeguard testing for OpenAI’s flagship launches, pilot new assurance mechanisms such as embedded auditing, run our misalignment disclosure process, and incorporate independent expert input as evidence for critical safety decisions.
As a Research Program Manager on the Frontier Assurance team, you will build programs that bring independent expertise into frontier AI safety decisions and make the evidence behind those decisions understandable to the public. You will lead external research partnerships and third-party assessments, coordinate public safety documentation, and develop new approaches to independent scrutiny and transparency.
What you'd do
- Design and run third-party assessment programs for frontier models and safeguards, including independent evaluations, adversarial testing, and new approaches such as embedded auditing.
- Work with researchers and external partners to define assessment questions, scope, access, timelines, and deliverables.
- Build and manage strategic research partnerships with third-party evaluators, academic labs, and other independent experts, prioritizing expertise, independence, and diversity of perspectives.
- Enable rigorous research, including work that challenges internal assumptions.
- Bring external findings to safety decision-makers and translate them into actionable recommendations for safeguards, deployment, product, and policy. Track follow-up actions and ensure partners understand how their input was considered.
- Partner with research, product, policy, and communications teams to explain the evidence behind OpenAI’s safety approach: what we tested, what we learned, how findings shaped safeguards and deployment decisions, and where limitations and uncertainty remain.
- Translate complex technical results into accurate, accessible communication for expert and public audiences.
- Lead public transparency programs, including system cards, summaries of third-party assessments, and updates on significant findings and follow-up actions.
- Develop approaches to sharing methods, results, and limitations while protecting privacy, security, and sensitive information.
- Create channels for researchers and civil society to ask questions, provide feedback, and inform future assessments and transparency efforts, including beyond individual launches.
- Own program goals, milestones, dependencies, and risks across assessment and transparency work, keeping internal and external stakeholders informed and resolving obstacles to execution.
- Have an understanding of AI evaluations and measurement, and can engage with technical teams on evaluation design and results.
- Can interpret evaluation findings and communicate what they do and do not establish, including methodological limitations, uncertainty, and disagreement.
- Have experience building research partnerships and managing external stakeholders, especially academic researchers and independent experts.