# Senior Solutions Architect, Generative AI

**Company**: NVIDIA
**Location**: Santa Clara, CA
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Solutions-Architect--Generative-AI_JR2022101?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/job/senior-solutions-architect-generative-ai-c64cd8ea-1c4/

## Description

NVIDIA is looking for a Senior Solutions Architect, Generative AI with deep, hands-on experience in large-scale GPU systems.

This role involves working with some of the world’s leading consumer internet companies and frontier labs building foundation models.

Primary responsibilities include:

- Accelerating customer workloads

- Designing high-performance AI infrastructure

- Leading technical engagements around NVIDIA technologies

The ideal candidate will have:

- 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

Responsibilities:

- Collaborate with customers to maximize GPU utilization and end-to-end workload throughput while improving infrastructure reliability and reducing infrastructure costs

- Design and optimize large-scale AI clusters across GPU compute, high-performance networking, storage, workload scheduling, orchestration, and observability

- Profile distributed training and inference workloads to identify bottlenecks across GPUs, CPUs, memory, network fabrics, storage systems, and software stack

- Diagnose complex infrastructure and distributed systems issues spanning InfiniBand and RoCE fabrics, cloud interconnects, RDMA, NCCL, NVLink, and NVSwitch

- Lead proof-of-concepts and performance studies for large-scale AI infrastructure, developing benchmarking tools, automation, runbooks, and technical collateral as needed

- Partner with NVIDIA’s engineering, product, and sales teams to secure design wins and drive innovative solutions based on customer requirements and field feedback

Requirements:

- 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

Nice to Have:

- 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

Benefits:

- Competitive salaries

- Generous benefits package

- Equity

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## Skills

### Required
- Linux systems
- distributed computing
- GPU architectures
- high-performance computing
- networking
- site reliability engineering
- Python
- shell scripting
- Kubernetes
- Slurm
- containers
- production monitoring systems
- InfiniBand
- RoCE
- GPUDirect RDMA
- NCCL
- NVLink
- NVSwitch

### Nice to have
- DGX/HGX systems
- Spectrum-X
- NCCL tests
- DCGM
- Nsight Systems
- fabric counters
- host- or switch-level diagnostics

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Solutions-Architect--Generative-AI_JR2022101?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)