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Job Details
Posted date: Jan 07, 2026
Location: Seattle, WA
Level: Senior
Estimated salary: $192,500
Range: $156,000 - $229,000
Description
Define and lead the entire roadmap and execution for storage and data optimizations for AI workloads (e.g., lower latency through caching (KV cache virtual expansion for TPUs, GPUs), faster model load times on GPUs and TPUs. Identify key features through customer engagement and GTM, specifically focused on channels for AI Infra (e.g., Kubernetes, vLLM, SGLang, PyTorch foundation). Build partnerships with the ecosystem to define AI infra standards and primitives (eg. data and storage well lit paths in llm-d, vLLM, SGLang). Stay updated on the latest research and propose new optimizations to accelerate transition from research to product.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.
Our goal is to build out industry infra primitives in Kubernetes for AI inference, agents and data workloads. By defining and delivering on these primitives, we enable Google Cloud to be the best cloud for AI workloads (inference, data and agents), while also allowing TPU in the broader ecosystem. This team had more then ten keynote launches (e.g., Inference Gateway, Run AI model streamer, vLLM/TPU, llm-d).
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.
The US base salary range for this full-time position is $156,000-$229,000 + 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.
Qualifications
Minimum qualifications: Bachelor's degree or equivalent practical experience.5 years of experience in product management or related technical role.
2 years of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc). Experience in the DevOps space.
Preferred qualifications: Master's degree in a technology or business related field. 3 years of experience in building and shipping technical products. 2 years of experience in AI infra with practitioner and knowledge of Cloud, Kubernetes, AI inference. Excellent communicator with a track record of distilling complex insights for consumption by customers, executives, sales, engineering.
Extended Qualifications
Bachelor's degree or equivalent practical experience.5 years of experience in product management or related technical role.
2 years of experience taking technical products from conception to launch (e.g., ideation to execution, end-to-end, 0 to 1, etc). Experience in the DevOps space.
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