About this role
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.
Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
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 Computer Science, Electrical Engineering, Systems Engineering, Applied Mathematics, or equivalent practical experience.
- 8 years of experience in program management.
- 6 years of experience in technical program management, systems architecture, or software engineering leadership.
Preferred qualifications:
- 8 years of experience managing cross-functional or cross-team projects.
- Experience writing and reviewing code (Python, SQL, JSON) and leveraging AI prototyping tools (e.g., Google AI Studio) for logic spec definitions.
- Proven track record of re-engineering complex, multi-tab spreadsheet ecosystems into production software applications.
- Bridge multi-year machine-level demand plans into data center power and space constraints. Operationalize location strategies (zone-level and global aggregation) without disrupting downstream delivery pipelines.
- Model complex allocation scenarios across key business segments, reconciling compute supply responses with site-level power and operational limits.
- Author and publish standardized operational playbooks to document tagging methodologies, deployment ramps, and capacity management mechanics into permanent institutional standards.
- Partner with Core Systems Engineering, DeciML, Data Science, and Operations teams to review design documents, establish technical specs, and drive User Acceptance Testing (UAT).
- Advocate for the adoption of practical AI workflows and modern tooling across the broader infrastructure team, providing technical mentorship to scale operational capacity.