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.

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.