Santa Clara, CAremote

Salary
$148,000–$235,750from the description
Posted
Jul 13, 2026
Location
Santa Clara, CA
Last confirmed open
Jul 20, 2026

What this job asks for AI summary

This role sits within a team responsible for validating new GPU-based AI infrastructure from initial hardware power-on through handoff to customers. Day-to-day work involves configuring and debugging multi-node Linux GPU clusters, running and analyzing AI/LLM benchmarks, investigating performance shortfalls in distributed training workloads, and building automation and observability tooling to support repeatable bring-up processes. It suits an experienced systems engineer with deep hands-on knowledge of GPU clusters, NCCL collective communications, and large-scale AI/ML workload troubleshooting.

Senior level · 6+ years · Remote · Full-time

Must have (9)
LinuxNCCLPythonShellPyTorch or TensorFlowmulti-GPU clustersdistributed systemsobservabilityAI/ML workloads
Nice to have (3)
HPCCI/CDGPU-accelerated computing

“or” means any one of them counts — you don't need all of them.

We read this from the posting text with AI. Skim the description below before ruling yourself out.

How this req sits in the market our data

Roughly 2,900 people nationally plausibly meet what this posting asks for (computer occupations, all other). range 600–4,350

Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.

What gives you an edge
PyTorch9%

Rare in this occupation — lead with these, and say what you built with them.

What won't set you apart
Python51%Linux45%

Most people in this occupation already list these. Still required — just not what gets you shortlisted.

What the occupation pays Median $119,144 (middle half $81,115–$160,963). This posting is about at that midpoint.

Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.

Why we read it this way (8)

The role title is 'Senior Solutions Architect' but the day-to-day work is deeply hands-on: running and debugging AI/LLM workloads, writing Python/Shell automation, building observability, and benchmarking GPU clusters — closer to a senior systems/infrastructure software engineer than a traditional solutions architect. SOC 15-1299 (Computer Occupations, All Other) is used as the best fit for this hybrid validation/bring-up engineering role; 15-1252 (Software Developers) is a credible runner-up given the automation and tooling development responsibilities.

The JD states 'Bachelor's degree or equivalent experience', so no formal degree is hard-required.

The '6+ years' figure is stated as a role-level experience gate against Linux-based systems in HPC/distributed/AI-ML settings, captured as the overall years minimum.

PyTorch and TensorFlow are listed as interchangeable examples ('frameworks such as PyTorch or TensorFlow') under the required qualifications section; PyTorch is named first and TensorFlow is captured as an alternative.

Shell and Bash are listed together in the JD ('Shell/Bash'); treated as a single skill with Bash as an alternative name.

Items under 'Ways to Stand Out From the Crowd' (HPC performance engineering, observability stacks, CI-style pipelines, AI-driven workflows) are preferred, not required.

Compensation includes equity in addition to the stated base salary range.

Caller marked this a fully-remote role — scored against the national candidate pool.

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