Technical Program Manager, Frontier Safety, Alignment and Collaboration, Deepmind

Google Google · Big Tech · Mountain View, CA +1

Technical Program Manager for Frontier Safety, Alignment, and Collaboration at Google DeepMind. This role focuses on operational strategy and execution for safe and responsible AI development, bridging AI research with product deployment. Responsibilities include managing safety frameworks, implementing unified safety gates, coordinating evaluations for critical capability levels, and managing mitigation plans for model breaches. The role requires strong program management skills and an understanding of ML/AI safety and alignment principles.

What you'd actually do

  1. Drive end-to-end program management and evolution of Google’s Frontier Safety Framework, balancing innovation with risk governance.
  2. Scale and implement unified safety gates across Google DeepMind, Research, and product pipelines for frontier model training and deployment while acting as the central interface for leadership updates on model risk posture, and collaborate with external policy, academic, and industry partners to align on global safety standards.
  3. Coordinate "early warning evaluations" to monitor Critical Capability Levels across core domains (autonomy, cyber, biosecurity, etc).
  4. Manage rapid mitigation plans for model CCL breaches, coordinating weight exfiltration security and misuse-limiting deployment protocols.
  5. Serve as the central liaison for leadership updates on model risks, collaborating with external policy, academic, and industry partners on global safety standards.

Skills

Required

  • 8 years of experience in program management
  • Bachelor's degree in a technical field, or equivalent practical experience

Nice to have

  • 8 years of experience leading large-scale engineering projects, preferably across multiple geographies and time zones.
  • Understanding of safety, alignment and other alignment related topics in ML.
  • Understanding of ML/AI principles and their distinctions from traditional software development.
  • Demonstrated success in changing program execution and deliveries.

What the JD emphasized

  • safe, responsible frontier AI development
  • bridge AI research with enterprise-wide product deployment
  • build operational structures from the ground up
  • safety, alignment and other alignment related topics in ML
  • Understanding of ML/AI principles and their distinctions from traditional software development

Other signals

  • operational strategy and execution of Google’s commitments to safe, responsible frontier AI development
  • lead highly technical, cross-functional initiatives that bridge AI research with enterprise-wide product deployment
  • build operational structures from the ground up to secure the next generation of foundation models
  • Scale and implement unified safety gates across Google DeepMind, Research, and product pipelines for frontier model training and deployment
  • Coordinate "early warning evaluations" to monitor Critical Capability Levels across core domains (autonomy, cyber, biosecurity, etc).
  • Manage rapid mitigation plans for model CCL breaches, coordinating weight exfiltration security and misuse-limiting deployment protocols.