Engineering Manager, Distillation & Dectection Platform

OpenAI OpenAI · AI Frontier · San Francisco, CA · Applied AI

Engineering Manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models, focusing on model IP protection, distillation detection, and emerging risks from autonomous agents. The role involves setting technical roadmaps, building scalable production systems, and partnering with Research and Product to translate model capabilities into deployed mitigations. Requires strong software engineering fundamentals, experience in adversarial environments, and leadership skills.

What you'd actually do

  1. 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.
  2. Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact.
  3. Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage.
  4. Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale.
  5. Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence.

Skills

Required

  • Significant experience leading engineering teams
  • delivering production systems end-to-end
  • Strong technical judgment in system design
  • distributed systems
  • data pipelines
  • observability
  • operational reliability
  • Demonstrated ability to partner cross-functionally with Research/Product/Security to ship systems that materially reduce risk or abuse at scale

Nice to have

  • 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.
  • 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.

What the JD emphasized

  • building production services
  • detection pipelines
  • mitigation mechanisms
  • frontier model integrity
  • reduce high-severity misuse risk
  • autonomous agents
  • systems in adversarial, fast-evolving environments
  • security
  • abuse prevention
  • fraud
  • integrity
  • platform defense
  • auth/identity
  • malware/spam
  • adversarial environments
  • model extraction / distillation
  • adversarial evaluation
  • scalable detection/mitigation approaches
  • autonomy
  • high-scale real-time systems
  • intelligence-adjacent technical domains

Other signals

  • building production services
  • detection pipelines
  • mitigation mechanisms
  • frontier model integrity
  • reduce high-severity misuse risk
  • autonomous agents