Senior Staff Program Manager, AI Infrastructure Investment Planning

Minimum qualifications:

• Bachelor's degree in a a technical field, or equivalent practical experience.
  
• 10 years of experience in program management, with a focus on planning and quantitative analysis.
• Experience in infrastructure planning (e.g., data centers, networks, compute capacity).
• Experience influencing cross-functional teams and executive stakeholders.

Preferred qualifications:

• 10 years of experience managing complex cross-functional or cross-team projects.
• 5 years of experience, within a hyperscale cloud or technology company.
• Strong financial acumen, including experience with cost-benefit analysis, business case development, and long-range capital planning.
• Expertise in data analysis, statistical modeling, optimization techniques, and simulation.
• Familiarity with the unique infrastructure requirements and challenges of AI/Machine Learning systems at scale.
• Understanding of data center technologies, power infrastructure, network architecture, and associated cost structures.

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 Program Manager at Google, you’ll lead complex, multi-disciplinary projects from start to finish — working with stakeholders to plan requirements, manage project schedules, identify risks, and communicate clearly with cross-functional partners across the company. Your projects will often span offices, time zones, and hemispheres. It's your job to coordinate the players and keep them up to date on progress and deadlines.

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 $221,000-$311,000 + 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.

• Lead the development, implementation, and refinement of sophisticated quantitative models and tools to optimize data center site selection, network planning, energy procurement, and supply chain strategies.
• Develop and prototype novel problem-solving approaches, including decision trees and AI-driven tools, to handle complex, multivariable problems like large-scale infrastructure planning, build and lease analyses, joint venture investment decisions, and risk mitigation.
• Drive strategic initiatives to maximize capital efficiency, reduce overall costs, and improve the on-time delivery of critical infrastructure.
• Influence and guide cross-functional teams across infrastructure, finance, and network planning to adopt data-driven decision-making processes and enhance planning frameworks.
• Provide expert analysis, strategic counsel, and clear recommendations to executive leadership on multi-year infrastructure asset plans, translating complex technical, financial, and operational trade-offs.