NVIDIA is a world‑leading, fast‑growing AI computing company, delivering everything from the most powerful GPU‑accelerated supercomputers to gigawatt‑scale AI data centers. We build and optimize end‑to‑end GPU server platforms that combine accelerated computing, high‑performance networking, and software to power state‑of‑the‑art AI infrastructure. We believe in our people and products, and we are looking for outstanding talent to join us.
We are seeking server and GPU infrastructure experts to join our Solutions Architect team. We are looking for a hands‑on, deeply technical engineer with strong experience in GPU servers, AI clusters, and data center infrastructure to help customers design, deploy, and optimize NVIDIA‑based AI factories. As a Server & GPU‑focused Solutions Architect, you will work closely with customers, partners, and internal engineering teams to turn NVIDIA platforms into production‑grade AI systems at scale.
What you will be doing:
- Lead presales and architecture engagements with AI industry customers, focusing on GPU servers, AI clusters, and large‑scale training/inference platforms built on NVIDIA HGX, GPU systems, and reference architectures.
- Design and validate end‑to‑end AI data center solutions, including server platforms, storage connectivity, and high‑performance networking based on Spectrum, Quantum, ConnectX, and BlueField.
- Define system architectures for AI supercomputing, LLM training, and inference workloads, including node configuration, GPU topology, PCIe/NVLink considerations, and network design.
- Support business teams in exploring, developing, and deploying NVIDIA server and GPU solution opportunities, from early technical discovery through POC and production rollout.
- Own and execute POCs and hands‑on labs that validate GPU server performance, scalability, reliability, and interoperability across compute, storage, and network domains.
- Troubleshoot complex end‑to‑end issues involving GPU servers, firmware, drivers, operating systems, and networking stacks, and drive fixes with internal R&D and partners.
- Provide structured feedback on platform features, system requirements, and customer needs to server OEMs, engineering, and product teams to improve NVIDIA AI platforms and ecosystems.
What we need to see:
- BS/BA in Computer Science, Electrical/Computer Engineering, or equivalent experience, with 6+ years of experience with data center servers, GPU platforms, or large‑scale AI/HPC infrastructure.
- Strong understanding of GPU server architecture: CPU/GPU balance, memory and PCIe/NVLink topology, storage and NIC placement, and power/cooling considerations.
- Proven experience designing or operating AI or HPC clusters using GPU‑accelerated servers in cloud or on‑prem data centers.
- Solid background in data center and cloud networking for AI workloads, including leaf‑spine fabrics, RDMA and high‑bandwidth/low‑latency designs.
- Strong Linux system and Linux networking skills, including driver, firmware, and OS‑level tuning for GPU and NIC performance.
- Knowledge and experience with K8S, RDMA/RoCE and, ideally, RoCE and Infiniband AI clusters.
- Excellent communication skills to collaborate with customers, server OEMs, and internal architecture and engineering teams.
Ways to stand out from the crowd:
- Knowledge with AI workflows
- Cloud infrastructure understanding and development experience
- Strong understanding of Kubernetes architecture (API server, etcd, controller manager, scheduler, kubelet, CNI)
- Coding experience with CUDA, RDMA applications
- Hands-on experience with NVIDIA networking solution stack
With competitive salaries and a generous benefits package, we are widely considered to be one of the world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you.