NVIDIA
Senior Solutions Architect, Generative AI
$184K–$356K
US, CA, Santa Clara +2 · Senior · Full-time · Posted Jul 30, 2026
- Location
- US, CA, Santa Clara
US, CA, Remote
US, WA, Remote - Experience
- 6+ years; related technical role areas are listed as alternatives.
- Education
- BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or another Engineering field, or equivalent experience.
About the job
Accelerates customer AI workloads by designing, optimizing, and troubleshooting large-scale GPU infrastructure and leading technical engagements.
What you'll do
- Optimize GPU utilization, workload throughput, infrastructure reliability, and cost with customers.
- Design and profile large-scale AI clusters and distributed training and inference workloads; diagnose infrastructure and networking issues.
- Lead proof-of-concepts and performance studies, and collaborate with engineering, product, and sales teams on customer solutions.
What they ask for
- BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or another Engineering field, or equivalent experience.
- 6+ years of experience in AI infrastructure, systems engineering, high-performance computing, networking, site reliability engineering, or a related technical role.
- Hands-on experience designing, deploying, operating, or troubleshooting high-performance GPU networks; experience debugging NCCL performance and profiling AI workloads.
- Experience with Kubernetes or Slurm, containers, production monitoring systems, and Python, shell scripting, or similar languages.
Nice to have
- Experience architecting and operating large-scale production GPU clusters for distributed training or inference.
- Expertise with NVIDIA infrastructure technologies and diagnostic tools such as DGX/HGX, NVLink, NVSwitch, NCCL, Spectrum-X, DCGM, and Nsight Systems.
Pay
184,000 USD - 287,500 USD (base salary, Level 4); 224,000 USD - 356,500 USD (base salary, Level 5)
Tools
Linux, InfiniBand, RoCE, GPUDirect RDMA, NCCL, Kubernetes, Slurm, Python
AI focus
Supports foundation-model customers by optimizing GPU infrastructure and distributed AI training and inference workloads.
Model-written summary · the original posting is authoritative