Senior Product Manager, AI Enablement and Infrastructure
Google Mountain View, California, United States · $192K–$278K/yr
Software Development · 10,001+ employees
About the role
Define product strategy and multi-year roadmaps for internal AI agent platforms, including runtimes and deployment gates. Lead cross-functional collaboration with engineering teams to identify operational bottlenecks and deploy automated agent solutions.
What they look for
Requirements
Requires a bachelor's degree and at least 8 years of experience in product management or a technical role. Candidates must have specific experience launching AI/ML products and driving developer-facing platforms.
Benefits
Full description
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in product management or related technical role.
- 3 years of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc).
- Experience developing or launching products or technologies within artificial intelligence or Machine Learning (AI/ML).
Preferred qualifications:
- Master's degree in a technology or business related field.
- 10 years of product management experience driving developer platforms, internal tools, infrastructure software, or machine learning systems.
- Experience collaborating with distributed systems engineering, hardware operations, or supply chain technical teams.
- Track record of taking developer-facing platforms from initial conception to broad multi-organization adoption.
- Strong communication skills with demonstrated success aligning cross-functional technical leaders on product strategy.
About the job:
At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.
In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.
One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.
As a Senior Product Manager for AI Enablement and Infrastructure, you will define the product strategy and technical roadmap for AI adoption across global systems and hardware infrastructure. You will partner with engineering teams across Data Center Operations, Supply Chain, and Compute Infrastructure to identify manual toil, translate operational workflows into reusable platform components, and deliver agent-based developer tools. In this role, you will define product specifications for core agent execution runtimes, context retrieval engines, and automated quality gates while delivering high-impact reference agents that demonstrate measurable operational gains.
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:
- Define product requirements and multi-year roadmaps for internal AI agent platforms, including agent runtimes, context indexing pipelines, and deployment gates.
- Partner with engineering leads across infrastructure, supply chain, and systems software to identify operational bottlenecks and deploy domain-specific automated agents.
- Establish platform product metrics for developer velocity, agent reliability, precision, recall, latency, and token cost attribution.
- Align requirements with central foundational model platform teams to integrate shared components and eliminate redundant tooling.
- Lead cross-functional working groups with senior technical stakeholders to prioritize platform capabilities, resolve architectural dependencies, and accelerate adoption.
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