Solutions Architect - AI Networking and Storage

NVIDIA NVIDIA · Semiconductors · TX +1 · Remote

Solutions Architect role focused on helping OEM customers build enterprise AI solutions using NVIDIA's AI technology, specifically focusing on the networking and storage demands for Generative AI, LLMs, and Deep Learning. The role involves architecting storage solutions, training partners, and acting as a technical authority on NVIDIA products, with an emphasis on high-performance storage systems and large-scale cluster bring-up.

What you'd actually do

  1. Closely coordinate with the OEM Global Account Managers (GAMs) in order to work on prioritized customer platforms, software stacks and solutions that map to critical business priorities
  2. Work with OEM partners to architect enterprise grade storage solutions with a focus on scalable performance and data durability
  3. Training OEM technologists and field specialists on AI storage and networking solution offerings from NVIDIA.
  4. Work as a key member of our OEM team as a technical authority on NVIDIA products
  5. Some travel to conferences and customers may be required (20%)

Skills

Required

  • BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience)
  • 8+ Years proven experience as a solution architect or technical presales role
  • Experience with Intel x86 and ARM architectures, networking, storage, and GPU solutions
  • Hands-on experience with high-performance storage systems: Lustre, GPFS, Ceph, distributed object storage, enterprise SAN/NAS
  • Excellent interpersonal skills, including the ability to explain complex technical topics to non-expert
  • Proven track record exemplifying how you have assisted customers from bring-up, through testing, through GTM readiness

Nice to have

  • Experience crafting and operating RDMA-accelerated HPC/AI clusters at scale, with hands-on expertise with network topologies and large-scale switch/router deployments
  • Background in jointly developing storage networks for AI/ML training pipelines, large-scale inference, and agentic AI workflows.
  • Proficiency in hybrid cloud storage and networking solutions (like Kubernetes CSI, cloud-native fabrics, and hybrid on-prem/cloud setups).
  • Experience with NVIDIA GPUs and software libraries, such as NVIDIA NIM, NVIDIA NeMo Framework, NVIDIA Triton Inference Server, TensorRT, TensorRT-LLM
  • Experience with large-scale cluster bring-up and operation.

What the JD emphasized

  • proven experience as a solution architect or technical presales role
  • Hands-on experience with high-performance storage systems
  • Proven track record exemplifying how you have assisted customers from bring-up, through testing, through GTM readiness
  • Experience crafting and operating RDMA-accelerated HPC/AI clusters at scale
  • Background in jointly developing storage networks for AI/ML training pipelines, large-scale inference, and agentic AI workflows.

Other signals

  • Enterprise AI solutions
  • Generative AI, LLMs, Deep Learning, and GPU technologies
  • Scalable performance and data durability for storage
  • AI storage and networking solution offerings