Engineering Manager, Preparedness

About the Team

The Preparedness Engineering team is responsible for building and operating safeguards for frontier model risks, to safely enable advanced capabilities while detecting and limiting harm.

About the Role

We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur. This is a builder’s role: you’ll lead engineers shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk.

While this work intersects with frontier model development, security and risk, we’re explicitly seeking someone with a software engineering foundation who is comfortable building reliable systems that can operate at billions of users scale.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will

• Lead a team of software engineers building detection + mitigation systems for frontier model harms.

• Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact.

• Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage.

• Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale.

• Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence.

• Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed.

• Anticipate what breaks at scale as agentic workflows become more capable.

You might thrive in this role if you

• Experience building systems in adversarial, fast-evolving environments

• Thrive in high context environments

• Are comfortable with ambiguity and novelty

• Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny.

• 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.

• Background in autonomy, high-scale real-time systems, or intelligence-adjacent technical domains is a plus.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated

Responsibilities

• Lead a team of software engineers building detection + mitigation systems for frontier model harms.
• Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact.
• Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage.
• Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale.
• Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence.
• Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed.
• Anticipate what breaks at scale as agentic workflows become more capable.

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.
• Thrive in high context environments.
• Are comfortable with ambiguity and novelty.
• Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny.

Preferred Qualifications

• Background in autonomy, high-scale real-time systems, or intelligence-adjacent technical domains is a plus.

• Relocation assistance to new employees