The opportunity
OpenAI’s mission is to ensure that artificial general intelligence benefits all of humanity. Safely delivering increasingly capable AI systems requires scalable technical safeguards, clear ownership of emerging risks, rigorous deployment readiness, and close coordination across…
What you'll do
Partner with product, engineering, research, and design to shape technical: roadmaps, long-term platform direction, and safeguards priorities across ChatGPT, API, enterprise, and cloud environments.
Translate product and safety objectives into execution plans that balance: near-term delivery, long-term platform evolution, customer needs, and responsible deployment.
Lead cross-functional programs end to end—from problem definition and: technical design through implementation, launch, iteration, and operational follow-through.
Own milestones, dependencies, risk mitigation, decision-making, and: accountability across engineering, infrastructure, integrity, trust and safety, legal, policy, operations, and go-to-market teams.
Partner with engineers on system architecture, public and internal APIs,: cloud deployment patterns, platform integrations, operational failure modes, and technical tradeoffs.
Drive the development, integration, or rollout of safeguards such as model: evaluations, post-training mitigations, classifiers, abuse detection, monitoring, enforcement workflows, human review, and agent-assisted review.
What they're looking for
- Coordinate readiness for sensitive or high-impact deployments, ensuring: appropriate safety coverage, escalation paths, operational controls, and alignment with external cloud or enterprise partners.
- Identify emerging misuse and severe-harm risks; define ownership and response: mechanisms across prevention, detection, investigation, enforcement, and continuous improvement.
- Establish meaningful metrics for program delivery, deployment readiness,: safety effectiveness, operational quality, and user or developer experience.
- Represent customer and developer needs in technical and leadership decisions,: balancing risk reduction, model usefulness, implementation complexity, speed, and scale.
