Engineering Manager, Distillation & Detection Platform

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. In this role you will: - Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with an emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. - 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 - Are comfortable with ambiguity and novelty - Have experience adjacent to security (e.g., abuse prevention, fraud, integrity, platform defense, auth/identity, malware/spam, adversarial environments) - 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. - Familiarity with model extraction / distillation, adversarial evaluation, or scalable detection/mitigation approaches. - 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. 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 Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the

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. Familiarity with model extraction / distillation, adversarial evaluation, or scalable detection/mitigation approaches. Ability to partner cross-functionally with Research, Product, and Security to ship systems that reduce risk or abuse at scale. Comfortable operating in adversarial, fast-evolving environments; ability to manage ambiguity and novelty; clear communication with senior stakeholders.

Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. 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 with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations 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. Anticipate what breaks at scale as agentic workflows become more capable.