Senior Solutions Architect, AI Infrastructure

NVIDIA•Redmond, WA

3d•$184,000 - $287,500

About The Position

NVIDIA is seeking an experienced, networking-savvy infrastructure Solutions Architect to help bring AI hardware and software technologies into production. The role supports accelerated networking for AI, machine learning, and HPC, and is part of the Solutions Architecture team. The architect will drive end-to-end technology solution integration with strategic technology customers, including cloud providers and hyperscalers.

Requirements

Bachelor’s, master’s, or doctoral degree in Electrical or Computer Engineering, Computer Science, Physics, or another engineering field, or equivalent experience.
At least 8 years of experience in Solutions Architect or similar technical pre-sales roles.
Strong sense of achievement, customer-oriented demeanor, and ability to drive technical pre-sales activities.
Practical knowledge of sophisticated networking for AI data centers, including GPUs, CPUs, InfiniBand and Ethernet fabric topologies, PCIe, host networking, and switches.
Experience with end-to-end compute and network performance debugging across hosts, switches, and optics.
Effective time management and ability to balance multiple tasks.
Ability to communicate ideas clearly through documents, presentations, and other formats.

Nice To Haves

External customer-facing skills and background.
Hands-on experience with NVIDIA Ethernet and InfiniBand networking hardware, NICs/HCAs, switches, and GPUs.
Good understanding of how system hardware architecture affects network performance, including kernel drivers, PCIe devices, NICs, DPUs, and GPUs.
Experience with large-scale GPU infrastructure deployments.
Experience designing and debugging at rack scale.

Responsibilities

Work with cloud providers and hyperscalers to develop, build, and deploy compute and networking solutions based on NVIDIA AI infrastructure hardware.
Work with customers on proofs of concept (POCs) for AI solutions that address critical business needs.
Conduct technical customer meetings covering new technologies and products, feature discussions, workshops, and performance debugging.
Provide recommendations to business and engineering teams on product strategy.