Google Technical Program Manager Jobs in California

Minimum qualifications:

• Bachelor's degree in a technical field, or equivalent practical experience.
• 8 years of experience in program management.
• Experience with artificial intelligence/machine learning projects, tools, or infrastructure.
• Experience creating and monitoring KPIs for AI products.
• Experience with AI model testing, evaluation, and tuning processes, as well as LLM release cycles and timeline management.

Preferred qualifications:

• 8 years of experience managing cross-functional or cross-team projects.
• Experience managing or deploying distributed workloads in hybrid cloud environments (e.g. spanning public cloud and on-premises infrastructures such as Google Distributed Cloud (GDC)).
• Experience with AI inference processes and model deployment optimization (e.g., model serving architectures, quantization, continuous batching, and utilizing hardware accelerators like GPUs/TPUs).

About the job
Google's projects, like our users, span the globe and require managers to keep the big picture in focus while being able to dive into the unique engineering challenges we face daily. As a Technical Program Manager at Google, you lead complex, multi-disciplinary engineering projects using your engineering expertise. You plan requirements with internal customers and usher projects through the entire project lifecycle. This includes managing project schedules, identifying risks and clearly communicating them to project stakeholders. You're equally at home explaining your team's analyses and recommendations to executives as you are discussing the technical trade-offs in product development with engineers.
Using your extensive technical and leadership expertise, you manage projects of various size and scope, identifying future opportunities, improving processes and driving the technical directions of your programs.
As a Technical Program Manager (TPM), you will lead the delivery of Generative AI products for enterprise customers. You will partner with product managers, engineers, and leadership to define roadmaps, prioritize features, dive deeper into the technical and product specifications, and drive complex technical projects to successful release.
In this role, you will navigate a fast-paced environment where your technical depth, product understanding, and program management expertise directly influence Google's AI strategy. You will be passionate about AI, skilled at managing complex programs, and ready to go deep technically on the product specifications. Help us empower developers to build the next generation of intelligent applications.
Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
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 .
Responsibilities

• Manage complex AI programs by applying deep technical and product understanding, leveraging this knowledge to identify efficiencies and provide thought leadership.
• Direct the entire project lifecycle-including requirement gathering, risk assessment, feature prioritization, and planning-to build cohesion and alignment across all stakeholders.
• Partner closely with engineering and product management to define workstreams, resource plans, and milestones, while delivering clear strategic updates to unique audiences and leadership.
• Utilize independent judgment to develop actionable, data-driven plans, proactively mitigate risks, resolve blockers, and design and implement processes that enable the team to scale.
• Manage high-impact customer engagements, advocate for innovative evaluation methodologies, and define Key Performance Indicators (KPIs) to drive data quality and programmatic success.

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