Technical Program Manager III, AI Modeling, Cloud Supply Chain

• Bachelor's degree or equivalent practical experience.
• 5 years of experience managing projects.
• Experience in developing AI/ML models, AI/ML algorithms, or AI-driven applications.

• 5 years of experience managing cross-functional or cross-team projects.
• Experience working with cloud computing platforms and developing solutions that interact with data warehouses and databases (e.g., SQL, NoSQL).
• Experience in Python and standard data science libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow/PyTorch).
• Experience with optimization techniques (e.g., linear programming, heuristic search) and simulation modeling.
• Experience or knowledge in global supply chain operations, planning, or logistics.

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.

As the Technical Program Manager for the Supply Chain Strategy and Innovation team, you will be responsible for transforming capabilities to plan, source, make, and deliver the vast network of hardware that powers cloud services. You will be responsible for developing, testing, and demonstrating working AI agent prototypes that solve high-impact business problems, which will then be transitioned to core engineering teams for production deployment.

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 force 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.

The US base salary range for this full-time position is $156,000-$229,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

• Design, build, and prototype AI agents focused on optimizing key supply chain functions for cloud compute infrastructure (e.g., forecasting, capacity planning, demand sensing, component procurement, logistics, and reverse logistics).
• Iterate on ideas, conducting A/B testing and proof-of-concept experiments to validate the technical feasibility and business impact of agent-based solutions.
• Collaborate with Data Science and Data Engineering teams to identify, clean, and structure the necessary supply chain data for use in ML and agent models.
• Create comprehensive documentation, including technical specifications, model architecture, and model maintenance procedures to ensure a seamless and efficient transition of successful prototypes to production engineering teams.
• Partner with Supply Chain Operations, Architects, Finance, and Engineering teams to define requirements, gather feedback, and ensure prototypes align with strategic business objectives and drive user adoption in production.