Senior Solutions Architect, Generative AI

NVIDIA; United States; Remote; USD 184,000 - 357,000; Full time

Job summary

NVIDIA Corporation in the United States is seeking an experienced AI infrastructure engineer to help customers maximize GPU utilization and throughput. You will design, deploy, and optimize large-scale AI clusters, and profile AI workloads to remove bottlenecks across GPUs, CPUs, memory, and networks.

You will diagnose complex infrastructure issues spanning InfiniBand, RoCE, RDMA, NCCL, NVLink, and NVSwitch, and lead proofs-of-concept with engineering and sales to secure design wins.

Qualifications

• BS, MS or PhD in CS/EE/Physics/Math or equivalent experience.
• 6+ years in AI infrastructure, HPC, networking, or related technical roles.
• Deep Linux and distributed computing knowledge for large AI clusters.

Responsibilities

• Collaborating with customers to maximize GPU utilization and throughput.
• Designing and optimizing large-scale AI clusters across GPUs, networking, storage, and orchestration.
• Profiling workloads to identify bottlenecks across compute, memory, and network layers.
• Diagnosing issues spanning InfiniBand, RoCE, RDMA, NCCL, and NVLink/NVSwitch.
• Leading proofs-of-concept and performance studies for AI infrastructure.
• Partnering with engineering, product, and sales to drive design wins.

Skills

Python

Shell scripting

Linux systems

Distributed computing

GPU architectures

Education

BS/MS/PhD in CS/EE/Physics/Math or equivalent

Tools

Kubernetes

Slurm

NCCL

InfiniBand

GPUDirect RDMA

DCGM

Nsight Systems

Job description

What You’ll Be Doing:

• Collaborating closely with customers to maximize GPU utilization and end-to-end workload throughput while improving infrastructure reliability and reducing infrastructure costs.
• Designing and optimizing large-scale AI clusters across GPU compute, high-performance networking, storage, workload scheduling, orchestration, and observability.
• Profiling distributed training and inference workloads to identify bottlenecks across GPUs, CPUs, memory, network fabrics, storage systems, and software stack.
• Diagnosing complex infrastructure and distributed systems issues spanning InfiniBand and RoCE fabrics, cloud interconnects, RDMA, NCCL, NVLink, and NVSwitch.
• Leading proof-of-concepts and performance studies for large-scale AI infrastructure, developing benchmarking tools, automation, runbooks, and technical collateral as needed.
• Partnering with NVIDIA’s engineering, product, and sales teams to secure design wins and drive innovative solutions based on customer requirements and field feedback.

What We Need To See:

• 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.
• Deep understanding of Linux systems, distributed computing, GPU architectures, and the hardware and software components of large-scale AI clusters.
• Hands-on experience designing, deploying, operating, or troubleshooting high-performance GPU networks in on-premises or cloud environments using technologies such as InfiniBand, RoCE, or GPUDirect RDMA.
• Experience debugging NCCL communication and distributed collective performance, including topology, transport, congestion, routing, and host-level configuration issues.
• Experience profiling AI workloads and identifying performance bottlenecks across compute, networking, storage, and orchestration layers.
• Experience with cluster schedulers and orchestration platforms such as Kubernetes and Slurm, along with containers and production monitoring systems.
• Proficiency with Python, shell scripting, or similar languages for infrastructure automation, benchmarking, and systems troubleshooting.

Ways To Stand Out From The Crowd:

• Experience architecting and operating large-scale production GPU clusters for distributed training or inference.
• Deep expertise with NVIDIA infrastructure technologies such as DGX/HGX systems, NVLink, NVSwitch, NCCL, InfiniBand, and Spectrum-X.
• Hands-on experience using tools and telemetry such as NCCL tests, DCGM, Nsight Systems, fabric counters, and host- or switch-level diagnostics to isolate performance and reliability issues.
• Understanding of network topology, congestion control, collective communication patterns, and their impact on distributed AI workload performance.
• Experience optimizing storage and data pipelines to sustain high-throughput training and inference workloads.

We make extensive use of conferencing tools, but occasional travel (20%) is required for local on-site visits to customers and conferences. We are open to remote work. We look forward to having you join our team!

With competitive salaries and a generous benefits package, NVIDIA is recognized as one of the technology world’s most sought-after employers. This role offers a chance to make a broad impact at NVIDIA by advancing innovation with our consumer internet & frontier labs partners. Are you inventive, diligent, committed, and driven? Do you enjoy tackling challenges? If so, we want to hear from you!

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 184,000 USD - 287,500 USD for Level 4; and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 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)