Technical Program Manager III, AI Transformation, Google Cloud

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.

The AI and Infrastructure (AI2) team at Google powers the global infrastructure behind all Google services and Cloud platforms. Our work spans the full spectrum of infrastructure engineering from designing and constructing gigawatt-scale data centers and petabit global networks, to engineering servers, optical switches, and AI accelerators, to building the infrastructure software that operates this worldwide fleet.

We are committed to delivering sustainable, secure, and resource-efficient infrastructure. Our mission is to maintain a safe and dependable foundation while ensuring Google's data center footprint dynamically scales with rapidly growing demand and honors our sustainability targets.

We are driving an organizational transformation of program management by modernizing workflows, embedding AI at the core of our operations, and engineering 'AI first' platforms. To support this initiative, we are seeking a Technical Program Manager (TPM) to architect, construct, and roll out transformative AI-native program management tools.

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.

US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

• Lead use-case analysis and author Product Requirements Documents (PRDs) to translate user needs into technical specifications. Design agentic workflows and tool integrations, collaborating with Engineering to deliver high-quality interfaces across surfaces that meet stringent performance standards.
• Establish deterministic evaluation metrics to benchmark and assess tool quality, analyze results, and resolve performance issues. Partner directly with end users to debug quality concerns.
• Coordinate product testing and phased launches for new AI capabilities. Oversee platform access controls and perform adversarial testing to evaluate agent failure modes, such as API payload errors and execution timeouts.
• Develop change management playbooks and direct targeted onboarding initiatives to drive adoption.
• Identify, communicate, and collaborate with relevant stakeholders within one or more teams to drive impact and work toward mutual goals. Build, maintain and enhance business, operational, and management dashboards.

• Bachelor's degree in a technical field, or equivalent practical experience.
• 5 years of experience in program management.
• Experience in software engineering, technical solution development or product development.
• Experience designing, building, and deploying AI models and intelligent agents.

• 5 years of experience managing cross-functional or cross-team projects.
• Experience driving internal tool adoption and executing structured change management strategies across large-scale engineering teams.
• Experience partnering with engineering teams to rapidly iterate, prototype, deliver and debug software solutions.
• Domain expertise in agentic development (e.g., enterprise RAG systems, Large Language Model (LLM) guardrails, and context management frameworks).