Senior Technical Program Management Lead, Trust Operations, Google Research

A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.

Google Research is working on some of the hardest problems in AI foundations, algorithms, science, health, crisis resilience, and much more.

The AI First Tooling & Governance team's mission is to accelerate the impact of teams with AI-first operational tooling and governance programs that ensure speed, scale, excellence, and safety are inseparable.

As the Google Research Trust Operations Lead you will be positioned to shape the launch standards and drive the day-to-day operations of privacy, security, and responsibility governance programs that serve Google Research and Google Labs.

This role serves as a critical bridge between operational execution and strategic program evolution - you will manage the process that ensures launch review compliance, completeness and efficiency, collaborate closely with central Privacy, Safety, and Security (PSS) teams, build a network of FTE advocates that can convert trust, and leverage AI technologies to scale program capabilities.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $192000 - $278000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google (https://www.google.com/about/careers/applications/benefits/).

Minimum qualifications:

- Bachelor's degree in a technical field, or equivalent practical experience.

- 8 years of experience in program management.

- Experience with products that achieve privacy, security, and data protection compliance.

- Technical experience in AI/ML system lifecycles, automated evaluation pipelines, or technical control verification.

- Experience managing operational teams, vendor operations, or extended workforces (TVC).

Preferred qualifications:

- 8 years of experience managing cross-functional or cross-team projects.

- Experience developing and communicating operational metrics, trade-offs, and roadmaps to senior stakeholders.

- Experience leading programs focused on user-focused business process automation in a compliance, privacy, or security environment.

- Experience developing program roadmaps, establishing project goals, and managing resource allocations.

- Demonstrated ability to influence cross-functional technical teams, manage stakeholders, drive project alignment, and develop and scale operational programs using automated tooling, AI, or advanced analytics.

- Advocate for the trust roadmap and collaborate across Alphabet to ensure it remains current with long-term protection strategies and aligns with product area-level OKRs tied to velocity and global impact.

- Oversee Privacy and Security operational programs within the Google Research and Labs product areas, owning strategic outcomes and ensuring alignment with product area-level compliance posture.

- Lead efforts to grow and scale governance programs by advocating for and leveraging in-house AI technologies, automation, and tooling optimizations.

- Transform high-friction manual review gates into 'well-lit paths' and automated self-service guardrails that accelerate research velocity.

- Architect and continuously optimize a risk-tiered governance delivery model across FTEs, extended workforce (TVCs), and autonomous AI agents—defining risk routing logic, exception escalation thresholds, and automated QA/SLO telemetry.