About the role

Our hiring partner is seeking a Senior Product Manager - AI & AI Infrastructure to lead product strategy and execution for cloud platforms serving AI workloads. This role requires demonstrated ownership of AI or AI infrastructure products, not simply general product management experience or use of AI productivity tools.

Location and work arrangement

This is a hybrid role available to candidates based in the Seattle area or the San Francisco Bay Area. Seattle is preferred; Bay Area candidates are welcome.

Key responsibilities

• Own product vision, strategy, prioritization and roadmaps for AI and cloud infrastructure capabilities.
• Translate enterprise customer needs and AI developer workflows into clear product requirements and measurable outcomes.
• Partner with engineering on infrastructure supporting model training, post-training, inference or agentic workloads, balancing performance, reliability, scalability and cost.
• Lead discovery, competitive analysis, product launches and adoption initiatives across technical and commercial stakeholders.
• Define product success metrics and use customer feedback and workload insights to guide investment decisions.
• Communicate technical trade-offs and product direction clearly to customers, engineers and executives.

Required qualifications

• Strong senior-level product management experience with demonstrated leadership of product strategy and end-to-end delivery.
• A track record of owning AI or AI infrastructure products, with clear examples of customer impact and product outcomes.
• Experience with cloud infrastructure and platforms such as AWS or Google Cloud Platform; both providers are not required.
• Relevant exposure to at least one of model training, post-training, inference or agentic AI workflows. Experience in all four areas is not required.
• Ability to evaluate infrastructure performance, scalability, reliability and cost trade-offs with engineering teams.
• Strong customer discovery, prioritization and cross-functional communication skills.
• Based in the Seattle area or San Francisco Bay Area and available for hybrid work.

Preferred technical context

• GPU infrastructure, accelerated computing or AI compute platforms.
• Kubernetes, Docker and container orchestration for AI workloads.
• Familiarity with model serving, compute scheduling, resource utilization or distributed systems.

Technical familiarity is assessed from a product-management perspective; this is not a software engineering role, and proficiency in Go or Python is not required.