Senior Product Manager, AI Infrastructure Capacity Platform

NVIDIA•Us, CA

About The Position

NVIDIA is seeking a Senior Product Manager to help shape and deliver a platform that supports how GPU and AI infrastructure is planned, allocated, and operated at scale. This platform provides visibility and control over infrastructure usage so teams can make better decisions about where and how capacity is deployed. In this role, you will collaborate across engineering, operations, data analytics, and product to define platform capabilities, navigate technical and operational tradeoffs, and drive adoption across a sophisticated infrastructure ecosystem. This is an excellent opportunity to apply AI and agentic techniques, data-driven decision making, and strong product sense to a product that improves infrastructure usage, efficiency, and readiness. The ideal candidate is a proven product manager who is deeply customer-centric, self-starting, and has exceptional product sense, and brings a high work ethic and positive demeanor to cross-functional collaboration.

Requirements

BS or MS (or equivalent experience) in engineering, computer science, management information systems, or another technical/quantitative field.
12+ years of related experience
Demonstrated track record of building customer-centric products, including direct work with users, internal collaborators, or enterprise customers.
Strong product sense, with the ability to identify high-value problems, craft coherent solutions, and make sound tradeoffs across user experience, business value, and technical feasibility.
Experience working directly with infrastructure, operations, or resource-focused products is essential. This includes allocation/quotas, observability, FinOps, or internal platforms.
You will drive adoption of early-stage or evolving platform products involving complex cross-functional collaborator groups.
Hands-on experience using AI tools to analyze data, explore product concepts, accelerate product workflows, or improve decision-making, plus the ability to create simple mockups, flows, or prototypes using tools like Claude, Figma, Sketch, whiteboarding tools, or AI-assisted design tools.
Strong analytical approach and communication skills, including experience defining metrics and using data to guide prioritization and product decisions, and a reputation for high ownership, strong work ethic, and a positive, collaborative, low-ego attitude.

Nice To Haves

Experience as a platform or infrastructure product manager in environments with many internal customers.
History of building internal tools or cross-functional operational platforms used by operations, business, or customer-facing teams.
Prior operational experience in infrastructure or capacity-related roles, such as operations or data center/cloud environments.
Experience working with cloud service providers (CSPs) and GPU/AI infrastructure.
Prior customer success, solutions engineering, or field-facing experience with infrastructure or platform products

Responsibilities

Own product strategy for core areas such as resource planning, operational workflows, platform visibility, and infrastructure analytics, and translate that strategy into a clear roadmap and prioritized backlog aligned with broader AI infrastructure goals.
Work closely with cross-functional collaborators to understand difficulties, find opportunities, and translate needs into shipped capabilities.
Define features with clear user stories, customer outcomes, technical requirements, and acceptance criteria, and drive end-to-end product development from discovery through delivery and adoption in ambiguous, fast-moving environments.
Define metrics, dashboards, and insights that improve decision-making, operational efficiency, and platform adoption.
Help define future platform capabilities and build simple UI mocks, flows, or prototypes using tools like Claude, Figma, Sketch, whiteboarding tools, or other AI-assisted design tools to convey user value, user experience, and design requirements.
Partner with engineering to navigate technical integrations, system constraints, and key performance aspects of the platform (reliability, scalability, responsiveness), modeling high ownership, strong follow-through, and a constructive attitude by surfacing risks early, resolving blockers, and building trust across teams.