Jobs / United States / Nvidia Corporation

Nvidia Corporation

Senior Solutions Architect, Networking and GPU System

4 Locations Posted today

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Skills this job asks for

NetworkingEnglishLinux

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 2,374 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Nvidia Corporation paid sponsored hires in similar roles62 certified filings for “Solutions Architect” (Sales Engineers) in CA: $139k–$199k, median $169k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 2,374 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Nvidia Corporation paid sponsored hires in similar roles
62 certified filings for “Solutions Architect” (Sales Engineers) in CA: $139k–$199k, median $169k. Most were filed at wage level IV (51%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

NVIDIA is a world‑leading, fast‑growing AI computing company, delivering everything from the most powerful GPU‑accelerated supercomputers to gigawatt‑scale AI data centers. We build and optimize end‑to‑end GPU server platforms that combine accelerated computing, high‑performance networking, and software to power state‑of‑the‑art AI infrastructure. We believe in our people and products, and we are looking for outstanding talent to join us. We are looking for a Senior Solutions Architect who is both customer‑facing and deeply hands‑on with SONiC‑based networking and GPU server infrastructure. In this role, you will partner with account and OEM partner teams to qualify opportunities, design solutions, run technical evaluations, and prove value to customers building large‑scale AI and HPC platforms. Supporting production clusters, including monitoring and troubleshooting, is also part of this role. What you will be doing: • Work closely with account managers to understand customer requirements, position our SONiC + Spectrum whitebox switch solutions, and shape technical win strategies for AI and HPC opportunities. • Design end‑to‑end architectures for customer proposals, including GPU server configurations, storage connectivity, and SONiC‑based leaf‑spine fabrics with RDMA/RoCE. • Build and validate hands‑on demos and POCs: deploy SONiC switches and GPU servers, configure networking, install software stacks, and run benchmarks to prove performance, scalability, and reliability. • Provide support for large-scale production SONiC switch clusters. • Own and manage customized SONiC software projects on Spectrum white-box switches. • Collaborate with internal engineering, product, and OEM partners to resolve complex issues in firmware, drivers, OS, routing, and GPU/network performance, then bring fixes back to active POCs. What we need to see: • BS/BA in Computer Science, Electrical/Computer Engineering, or equivalent practical experience. • 6+ years in data center or cloud infrastructure roles (solutions architect, systems engineer, network engineer) with direct exposure to presales or customer‑facing technical work. • Solid background in data center networking for AI workloads: leaf‑spine designs, high‑bandwidth/low‑latency fabrics, RDMA/RoCE, and ideally InfiniBand; comfortable configuring and debugging these in lab and customer environments. • Practical knowledge of SONiC: installing and upgrading, configuring interfaces and routing (BGP/EVPN/VXLAN), using monitoring/telemetry tools, and troubleshooting real incidents. • Strong, practical understanding of GPU server architecture: CPU/GPU balance, memory bandwidth, PCIe/NVLink topology, storage and NIC placement, and power/cooling at rack level. • Hands‑on experience designing, deploying, or operating AI/HPC clusters using GPU‑accelerated servers (on‑prem or cloud), including real involvement in sizing, configuration, and performance tuning. • Excellent communication and presentation skills: able to explain complex technical topics to both highly technical engineers and non‑technical decision makers, and write clear design documents and POC reports. Fluent written and spoken English is required. Ways to stand out from the crowd: • Contributions to open‑source SONiC, networking, or AI infrastructure projects, or published talks/whitepapers on AI data center design and performance tuning. • Coding experience on SONiC. • Coding experience with NCCL, NIXL or other collective communication library, RDMA applications, or performance‑critical distributed training frameworks, giving you credibility when discussing low‑level performance with customer engineers. • Hands‑on deployments of SONiC in production or large lab environments, especially integrated with GPU clusters an

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