Senior Solutions Architect, AI Infrastructure

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +2

Senior Solutions Architect role at NVIDIA focused on architecting and scaling AI infrastructure, particularly GPU-based systems for deep learning inference, for customers. The role involves technical customer engagement, supporting sales, and providing onsite support.

What you'd actually do

  1. Help architect and scale high-performance, distributed AI infrastructure on-prem or in the cloud built with the latest NVIDIA GPU supercomputers for new and existing customers.
  2. Be a technical specialist on GPU and networking products, directly supporting sales account managers to secure design wins.
  3. Actively establish and nurture technical relationships with engineers, management, and architects at key customer accounts.
  4. Identify customer architectures and key product requirements in the CSP/OEM AI market to successfully implement NVIDIA's solutions.
  5. Provide onsite support to solve hardware and software problems, with a focus on deep learning inference.

Skills

Required

  • BS or MS in Engineering, Electrical Engineering, Physics, or Computer Science (or equivalent experience)
  • 8+ years of work-related experience in the high-tech electronics industry, particularly in system design or technical customer support roles
  • Expert analytical and problem-solving abilities
  • Strong time-management and interpersonal skills for coordinating complex projects
  • Excellent written and oral communication skills in English

Nice to have

  • Experience with ARM and NVIDIA GPU development
  • Proficiency in C/C++ and Python programming
  • Knowledge of Embedded Linux Systems, APIs, and similar embedded OS
  • Practical knowledge of NVIDIA systems technology such as NCCL, DCGM, UFM
  • Experience working with OEMs in industrial, military, and ruggedized computing spaces

What the JD emphasized

  • deep learning inference
  • GPU products
  • AI infrastructure

Other signals

  • customer-facing technical role
  • architecting and scaling AI infrastructure
  • GPU and networking products
  • deep learning inference