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NVIDIA

Designs the chips and software that power AI

Senior Solutions Architect

Full-TimeUpdated on 10/15/2026
No salary listed
Senior
Bachelor's
Beijing, China+1 moreMore locations: Shanghai, China
In Person
Solution EngineeringImplementation & Technical Account Management

About the job

Requirements
  • At least 5 years of work experience and a bachelor's degree in Engineering or Computer Science, or comparable experience.
  • Strong knowledge of network interface cards and data processing units, including their hardware architecture, capabilities, deployment models, drivers, firmware, and diagnostic tools.
  • Solid understanding of SmartNIC/DPU offload technologies, including RDMA, RoCE, TCP/UDP offload, overlay offload, encryption offload, virtual switching offload, and flow-processing acceleration.
  • Strong knowledge of Ethernet and data center networking protocols, including Layer 2/Layer 3 forwarding, VLAN, VXLAN, TCP/IP, UDP, ARP, IPv6, MTU, and Jumbo Frames.
  • Familiarity with network virtualization and acceleration technologies, including SR-IOV, VirtIO, vDPA, PCIe passthrough, IOMMU, PF/VF, RSS, RPS, XPS, DPDK, SPDK, Open vSwitch, and OVS-DPDK.
  • Familiarity with virtualization and cloud-native networking environments, including KVM, VMware, Kubernetes, CNI, Multus, SR-IOV CNI, OpenStack Neutron, OVN, and NFV.
  • Familiarity with server platform technologies, including BIOS, BMC, UEFI, Redfish/IPMI, Secure Boot, firmware lifecycle management, system bring-up, and hardware compatibility validation.
Responsibilities
  • Drive technical engagement, solution design, and deployment of NVIDIA networking products, including ConnectX NICs, BlueField DPUs, and related software stacks.
  • Understand customer networking requirements across AI, HPC, cloud computing, storage, virtualization, container platforms, and enterprise data centers.
  • Design and validate end-to-end network architectures connecting servers, switches, NICs, DPUs, GPUs, and storage systems, from single-node deployments to large-scale clusters.
  • Support proof-of-concept projects, cluster bring-up, performance validation, deployment readiness, production issue resolution, and customer acceptance testing.
  • Analyze network performance, including throughput, latency, packet loss, congestion, RDMA efficiency, and system bottlenecks.
  • Provide architecture and optimization guidance for NIC virtualization, hardware offload, RDMA, RoCE, DPDK, SPDK, Open vSwitch, and related technologies.
  • Work with product, software, firmware, driver, systems engineering, and sales teams to resolve customer issues and improve solution readiness.
  • Collaborate with OEMs, ODMs, switch vendors, server vendors, and software partners on platform compatibility, firmware, BIOS/BMC configuration, PCIe topology, and system validation.
  • Develop technical presentations, solution guides, deployment documentation, performance reports, best-practice materials, and customer training content.
  • Gather customer requirements and field feedback related to product functionality, performance, interoperability, manageability, and deployment challenges.
Desired Qualifications
  • Hands-on experience with lossless Ethernet and congestion-management technologies, including QoS, PFC, ECN, DCQCN, traffic shaping, queue management, and congestion control.
  • Experience designing, deploying, and troubleshooting Leaf-Spine, Clos, L2/L3 Fabric, AI cluster, RoCE, or InfiniBand network topologies.
  • Familiarity with NVIDIA networking and GPU technology.
  • Strong leadership and project management skills.
  • Excellent communication skills and ability to work across diverse teams.

About the company

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify Jobs

Simplify's Take

What believers are saying

  • AI demand is still surging: data center sales rose 117% to $89 billion in the quarter ending July 2026.
  • Stock grants are worth more: shares hit a record in October 2026, up 28% for the year.
  • Engineering dominates hiring: 1,722 of NVIDIA's 2,686 job listings in October 2026 were in engineering.

What critics are saying

  • Big buyers are hedging: Meta's February 2026 agreement covers 6 gigawatts of AMD chips.
  • Financing its buyers is getting harder: lenders pushed back on NVIDIA's $500 billion chip-backed loan plan in October 2026.
  • Staff described long hours: Bloomberg's August 2024 interviews reported seven-day weeks, late nights and shouting matches.

What makes NVIDIA unique

  • Rivals must match its software too: over 7.5 million developers use CUDA and other NVIDIA tools to program its chips.
  • The CEO has a broad direct staff: Jensen Huang says over 60 people report to him, without one-on-ones.
  • People rarely leave: NVIDIA's yearly staff turnover is 3.7%, versus a 21.9% average across the tech industry.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-1%

2 year growth

-2%
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