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OpenAI's Preparedness Engineering team is seeking an Engineering Manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models. This is a hands-on builder's role focused on shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk at scale.
In this role, you will lead a team of software engineers building detection and mitigation systems for frontier model harms. You'll set the technical roadmap and execution strategy, prioritizing and designing systems that ship and iterate with measurable impact. You'll build production systems including services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage across billions of users.
You'll partner deeply with Research and Product teams to translate evolving model capabilities into concrete tests, signals, and mitigations deployable at scale. You'll drive strong engineering fundamentals across architecture, reliability, monitoring, performance, and operational excellence. You'll hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed, and anticipate what breaks at scale as agentic workflows become more capable.
The role is based in San Francisco with a hybrid work model of 3 days in the office per week. OpenAI offers relocation assistance to new employees.
QUALIFICATIONS & REQUIREMENTS:
- Significant experience leading engineering teams and delivering production systems end-to-end
- Strong technical judgment in system design, distributed systems, data pipelines, observability, and operational reliability
- Demonstrated ability to partner cross-functionally with Research/Product/Security to ship systems that materially reduce risk or abuse at scale
- Experience building systems in adversarial, fast-evolving environments
- Ability to thrive in high-context environments and communicate clearly with senior stakeholders
- Comfort with ambiguity and novelty; pragmatic, collaborative, and calm under scrutiny
- Background in autonomy, high-scale real-time systems, or intelligence-adjacent technical domains is a plus
