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.
We are seeking a visionary, highly strategic, and operationally rigorous Senior Leader to help transform our AI data ecosystem. This critical role bridges the gap between insights from our frontline human data generation domain experts, data collection operations and our core AI research, data science, and engineering organizations. Successful candidate should be able to transform raw feedback from domain experts into actionable market intelligence that helps improve tooling infrastructure and provides insights into AI model improvement areas.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving team behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
****Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $240000 - $334000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Define and execute the end-to-end strategy for capturing qualitative and quantitative insights from the expert pools globally.
- Act as a strategic thought partner collaborating with research scientists, data scientists, and software engineering leads to convert expert-derived insights into product roadmap, and improved model training/evaluation methodologies.
- Design and embed frictionless, real-time feedback mechanisms directly within core data generation tool to capture insights instantly across projects.
- Build and manage a central knowledge hub on human data trends, methodologies, and competitor insights through expert focus groups, interviews, and vendor assessments.
- Serve as AI Data Operations leader in the US representing the team in all strategic conversations around human data, bridge the gap by alignment with other team members and leaders globally.
Qualifications
Minimum qualifications:
- Bachelor's degree in a technical field, or equivalent practical experience.
- 10 years of experience in program management.
- Experience working with data structures or machine learning algorithms.
Preferred qualifications:
- Experience in understanding Gen AI and Agentic AI workflows with experience around workflow design and improvement.
- Experience managing or collaborating with highly specialized domain expert pools (e.g., legal, medical, finance, marketing etc.) with knowledge of best practices on leveraging the human data generated for driving model performance.
- Expertise in both qualitative and quantitative research methodologies (e.g., focus group discussions, psychometrics, survey design, and structured interviewing).
- Robust understanding of Gen AI and Agentic AI with firsthand experience in partnering with research scientists, data scientists, engineering teams to build and train AI models.