# Senior Solutions Architect, GPU System

**Company**: NVIDIA
**Location**: Beijing, Shanghai
**Work arrangement**: onsite
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/China-Beijing/Senior-Solutions-Architect--GPU-System_JR2015505?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_d2ee48f6-dc9

## Description

We are seeking a Senior Solutions Architect to join our Solutions Architect team. This role involves leading 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.

Key responsibilities include:

- 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.

Requirements include:

- 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.

## Skills

### Required
- GPU server architecture
- AI clusters
- Large-scale training/inference platforms
- NVIDIA HGX
- GPU systems
- Reference architectures
- Spectrum
- Quantum
- ConnectX
- BlueField
- Node configuration
- GPU topology
- PCIe/NVLink considerations
- Network design
- POCs
- Hands-on labs
- GPU server performance
- Scalability
- Reliability
- Interoperability
- Compute
- Storage
- Network domains
- Firmware
- Drivers
- Operating systems
- Networking stacks
- Server OEMs
- Engineering
- Product teams
- K8S
- RDMA/RoCE
- RoCE
- Infiniband AI clusters
- Linux system
- Linux networking
- Driver
- OS-level tuning

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/China-Beijing/Senior-Solutions-Architect--GPU-System_JR2015505?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)