Senior Solutions Architect, First Time Deployment Validation - NVIS
Nvidia
Listing collected from Nvidia's career site. NextChapter is independent of Nvidia.
Remote · Santa Clara, CA · Posted October 6, 2026
Just laid off? Start here: a plan for the first weeks
More in California job market · All Senior Solutions Architect jobs (90) · Technology & Software · Engineering jobs
More roles at Nvidia
- Senior PR Manager, Enterprise AI Models · Santa Clara, CA
- Senior Technical Program Manager, Data Center - Engineering Operations · Santa Clara, CA
- North America Logistics Execution Program Manager · Santa Clara, CA
- Senior Manager, PR - AI Software · Santa Clara, CA
- Senior Developer Relations Manager - Telecom · Santa Clara, CA
- Senior Product Manager, Inference Platform · Santa Clara, CA
Similar jobs
- Sr. IT Systems Engineer- Palmdale, CA- Secret Required · Sikorsky Aircraft · Palmdale, CA
- Staff IT Systems Engineer- Palmdale, Ca- Secret Required · Sikorsky Aircraft · Palmdale, CA
- Solutions Engineer, APO - Bay Area · Cisco Systems · San Francisco, CA
- Solutions Engineer - Splunk (Remote) · Cisco Systems · San Jose, CA
- Principal Systems Engineer – Chief Engineer (Onsite) · RTX · el segundo, CA
- Systems Engineer I - Electronic Warfare · RTX · goleta, CA
Where Santa Clara, CA ranks
Where Santa Clara, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for sales pay after cost of living$175k · of 45
- #1Best cities for product pay after cost of living$224k · of 14
- #2Best cities for operations pay after cost of living$173k · of 41
- #2Best cities for marketing pay after cost of living$192k · of 16
- #2Best all-round cities for remote workers in the West Coast85 / 100 · of 39
- #3Best cities for finance pay after cost of living$156k · of 35
Rankings about engineering jobs
- Best cities for software and engineering jobs #1 San Francisco (3,412 openings)
- Best cities for engineering pay after cost of living #1 San Mateo ($216k)
- Most requested AI skills in engineering jobs #1 AI tools in daily work (6.1%)
- AI tools named most often in engineering jobs #1 Claude (1.7%)
- Employers with the most engineering jobs #1 Amazon (2,992 roles)
Pay compared with the market
This listing does not state pay. Across 29 open senior solutions architect listings that state pay, the middle half runs $154,000 to $236,000 and the median is $176,500.
Listed pay is what employers advertise, not what people are paid.
Senior Solutions Architect salaries by state · Check your own pay
How AI is used in this kind of work
Among computer occupations, all other, AI is already used for a large share of the tasks. Measured exposure for computer occupations, all other: 31% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
Say which you have and which you want to build. We use it to match you to jobs like this one.
About the job
We're looking for an ambitious Senior Solutions Architect to drive validation of NVIDIA AI factories from first rack power-on through customer handoff. You will be embedded in launches from the start, running and debugging AI/LLM workloads and benchmarks on Linux-based GPU clusters using NCCL and collectives (AllReduce, AllToAll) to validate performance and scalability. When workloads or benchmarks fall short, you're the expert who digs in, partners with engineering, and drives resolution. You will operationalize observability and automation to accelerate validation, capture structured evidence across every bring-up milestone, and work directly with internal deployment teams and external customers to ensure AI factories are ready at launch. Your work directly enables the success of NVIDIA's first external product launches! What You Will be Doing: Set up, adjust, and verify AI factory environments across multi-GPU and multi-node Linux clusters. Ensure configurations align with guidelines for NCCL, collectives, and distributed training frameworks. Own the execution of key AI/LLM benchmarks, including setup, orchestration, result collection, and analysis. Investigate and resolve issues when training jobs or benchmarks fail, hang, or underperform. Build and improve observability for AI factories (metrics, logs, traces, dashboards) to understand workload behavior and system health. Develop automation (Python, Shell) for running benchmarks, collecting results, and performing regression checks Examine communication patterns and NCCL usage for AI/LLM workloads, concentrating on collectives such as AllReduce and AllToAll. Recommend changes to job configuration, parallelism strategies, and cluster settings to improve throughput, latency, and scaling efficiency. Work closely with hardware, software, networking, datacenter, and product teams to prepare AI factories for customer use. Contribute to documentation, guidelines, and readiness collateral that support internal collaborators and customer-facing teams. What We Need to See: Bachelor’s degree or equivalent experience in Computer Science, Mathematics, Engineering, Physics, or related field. More than 6+ years of experience managing Linux-based systems in HPC, distributed systems, or extensive AI/ML settings. Hands-on experience running AI/ML workloads on multi-GPU and/or multi-node clusters, with practical knowledge of NCCL. Solid grasp of collective communication patterns, particularly AllReduce and AllToAll, and how they are applied in contemporary ML/LLM training. Familiarity with LLM training and/or inference workflows using frameworks such as PyTorch or TensorFlow. Proficiency with Python and Shell/Bash for scripting, automation, and tooling. Experience with benchmarking (crafting, executing, and interpreting performance benchmarks). Comfortable working with observability data (metrics, logs, dashboards) to troubleshoot and optimize complex distributed workloads. Strong communication skills and the ability to work effectively with cross-functional teams. Ways to Stand Out From the Crowd: Experience with AI factory or large-scale AI infrastructure build, deployment, or operations. Background in HPC performance engineering, SRE, or systems performance analysis for GPU-accelerated environments. Familiarity with observability stacks (e.g., metrics/monitoring, logging, tracing systems) used for large distributed systems. Experience building automation and CI-style pipelines for running and validating benchmarks at scale. Demonstrated desire to use AI to solve practical problems, improve workflows, and guide data-driven decisions. NVIDIA is widely considered one of the technology world’s most desirable employers. Some of the world's most forward-thinking and hardworking people are working for us. If you're creative and autonomous, we want to hear from you. #BuildTheAIFactory Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 148,000 USD - 235,750 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 10, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.