Senior Product Marketing Manager, AI Infrastructure

NVIDIA•Santa Clara, CA

About The Position

NVIDIA is seeking a Senior Product Marketing Manager focused on AI infrastructure solutions, spanning data center GPUs, rack-scale systems such as MGX and NVL platforms, and full AI factory reference designs. The role positions NVIDIA’s full AI infrastructure stack, connecting GPU architecture and system capabilities to rack-level and data-center-level outcomes. It communicates how co-design across compute, networking, memory, power, cooling, and software can deliver performance and efficiency, including the economics of tokens per dollar and performance per watt. The position leads product marketing and go-to-market launches across the AI infrastructure portfolio. It works closely with engineering, sales, creative, product management, and ecosystem partners to develop positioning and content for agentic AI and high-performance computing audiences. The role also supports press, analyst, and executive communications, and is responsible for rigorous, consistent substantiation of technical performance and efficiency claims. The successful candidate will combine technical knowledge of data-center infrastructure with business insight, communicating clearly with audiences ranging from press and analysts to technical teams, sales, and customers. NVIDIA offers competitive salaries, equity, and benefits. Applications will be accepted at least until November 10, 2026. This posting is for an existing vacancy.

Requirements

Bachelor’s or Master’s degree in engineering, or equivalent experience.
12+ years of relevant work experience.
Background and prior work experience in data-center marketing or AI infrastructure.
Working knowledge of data-center infrastructure beyond accelerators, including rack architecture, power delivery, cooling, interconnect, and deployment constraints.
Strong combination of technical knowledge and business intelligence, with comfort engaging marketing, engineering, and product management teams.
Past success working across major internal functional areas.
Demonstrated ability to work with engineering teams to extract key value propositions.
Ability to explain AI factory technical concepts and value propositions clearly and concisely to general press, analysts, technical press, sales teams, and end customers.
Demonstrated rigor with technical claims and competitive positioning.

Nice To Haves

Experience with agentic AI, inference at scale, deep learning, and NVIDIA GPUs.
Understanding of agentic workloads and their infrastructure requirements, including tool calling, orchestration, long-context inference, and related CPU, memory, and networking behavior.
Experience with rack-scale or data-center infrastructure, such as liquid cooling, high-voltage power distribution, or open standards work such as OCP.
Experience positioning infrastructure as an investment, including TCO modeling, ROI narratives, or customer deployment and financing economics.
Experience building executive-level and press-facing content under launch timelines.

Responsibilities

Lead product marketing and go-to-market launches across NVIDIA’s AI infrastructure portfolio, including data-center GPUs, rack-scale systems, and AI factory reference designs.
Build positioning that connects silicon and system capabilities to rack-level and factory-level customer outcomes.
Explain how co-design across compute, networking, memory, power, cooling, and software delivers system-level results.
Work with engineering, sales, creative, and product management teams to create web content, launch materials, keynote content, and other marketing assets for agentic AI and high-performance computing applications.
Engage engineering teams to understand technical details and identify key value propositions.
Develop and defend performance and efficiency claims by establishing baselines, verifying figures across sources, and maintaining consistency across materials.
Support press briefings, analyst engagements, and executive content, including messaging documents, Q&A, and FAQs for technical audiences.
Partner with OEM, ODM, cloud, and ecosystem teams on joint positioning and launch activities.
Evangelize new approaches to AI infrastructure marketing to technical and business audiences, internally and externally.
Communicate the economics behind AI factory investment, including tokens per dollar and performance per watt at rack and factory scale.