This is an opportunity to join DeepMind and architect the multi-quarter product goal, organizational strategy, and platform portfolio for AI Security and Privacy Platforms across our frontier models, autonomous agent frameworks, eval infrastructure, and confidential compute ecosystems. As artificial intelligence systems evolve into autonomous agents capable of multi-step tool use, code execution, and persistent cross-device context, establishing resilient containment, runtime oversight, and hardware-verifiable privacy is essential to maintaining global trust and safely expanding the frontier of AI.
As a Group Product Manager (GPM), you will lead a high-leverage product roadmap embedding agentic security and privacy-preserving architectures directly into the core AI lifecycle—from reinforcement learning and eval environments to runtime trajectory monitoring, context lineage tracking, and confidential cloud serving. You will establish product excellence at the convergence of frontier AI, security and privacy, and governance.
Artificial intelligence will be one of humanity’s most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $240000 - $333000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Define and own the multi-quarter product goal, charter, and roadmap for Agentic Security and Privacy Platforms across frontier training and evaluation pipelines, developer tools, and deployments to end-users.
- Build secure execution environments across evaluation, reinforcement learning, and developer command-line interface workflows by enforcing hardened sandboxes, strict network access controls, and least-privilege permissions.
- Lead unified runtime monitoring platforms—combining reasoning-trace oversight, prompt injection defenses, and fine-grained context lineage tracking.
- Scale automated adversarial testing platforms to systematically stress-test agent behaviors, paired with verification and safe production deployment.
- Lead the platform roadmap for hardware-enforced confidential artificial intelligence inference—including secure hardware enclaves, remote attestation, and encrypted transport—alongside privacy and safety guardrails for enterprise and sovereign clouds.
Minimum qualifications:
- Bachelor's degree in Computer Science, Engineering, a related technical discipline, or equivalent practical experience.
- 10 years of product management experience, including experience leading platform or infrastructure products across AI/agentic security, confidential computing, systems security, cyber security, or privacy engineering contexts.
Preferred qualifications:
- Experience deploying real-time safety guardrails and verifiable security and privacy controls across cloud, airgapped, or confidential compute environments.
- Exceptional executive communication and stakeholder alignment skills; proven ability to drive cross-functional alignment across technical and non-technical executive leadership.
- Proven ability to steer multi-quarter strategic portfolios bridging deep foundational research bets with enterprise-grade and consumer-scale production deployments.
- Deep technical fluency in agentic security paradigms (e.g., sandbox hardening, runtime reasoning and action monitoring, prompt injection resilience, dynamic information-flow tracking, or automated red-teaming and remediation workflows).