Engineering Manager, Safeguards Interventions

Key Responsibilities

• Hands-on lead and grow a team of engineers; own roadmap, OKRs, and execution.
• Drive cross-functional work with ML Infra, Research, Product, Policy, and Legal - and with cloud partners for 3P deployment.
• Set the bar for when an intervention is good enough to ship - backed by measurement - and represent safety and product tradeoffs to leadership and external stakeholders.
• Own production reliability for intervention and compliance systems: incident response, postmortems, SLOs, and the verification processes that prevent repeat incidents.

Minimum Qualifications

• Have managed engineering teams shipping production ML or safety-enforcement systems where the system's decisions directly affected users.
• Have run high-stakes, compliance-adjacent production systems: comfortable with on-call, incidents, regulator-driven requirements, and building the process scaffolding that prevents recurrence.
• Care about measurement: you've built (or insisted on) the evals that prove a system does what it claims, and you've killed things that didn't.
• Can drive ambiguous, multi-stakeholder tradeoffs (safety vs UX vs latency vs cost) to a decision and own the outcome.
• Care deeply about AI safety and want your team's work to be the reason advanced models can be deployed at all.

Preferred Qualifications

• Have worked in trust & safety, integrity, or abuse-prevention engineering at scale.
• Experience with compliance-driven systems (child safety, copyright, age assurance) and the legal/policy interfaces they require.
• Have shipped systems across multiple cloud providers and understand the parity/verification problems that creates.

Education

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience