Senior Solutions Architect, AI Factory Infrastructure

NVIDIA NVIDIA · Semiconductors · Durham, NC +3 · Remote

This role focuses on designing and implementing AI infrastructure solutions for customers, with a strong emphasis on AI inference at scale and physical AI simulations. It involves full-stack design, including hardware, workload orchestration, and application performance tuning, for hybrid cloud and on-prem deployments.

What you'd actually do

  1. Help customers with their AI factory journey, including workflow pipelines and performance optimization
  2. Focus data center implementations for inference use cases, including distributed, disaggregated and scaled out workflows
  3. Scope physical AI journeys on Omniverse, including synthetic data generation, data aggregation, application development and simulation pipelines
  4. Lead technical sales activities for AI factories with focus on hybrid deployments between cloud and on-prem
  5. Deliver hybrid cloud architectures for data pipelines, storage, security and user streaming connectivity

Skills

Required

  • Bachelor's degree or equivalent experience in Engineering or Computer Science
  • 15+ years of meaningful work experience, ideally in an IT infrastructure or related field of expertise
  • Expertise with infrastructure management including Linux, Kubernetes, Ethernet networking, and tools built for cloud environments
  • Strong experience with Linux system environments, using Linux as a core operating system for IT workload delivery
  • Confident with Python programming, specifically interfacing with IT infrastructure through API, SDKs and libraries
  • Mastery of how software and hardware work together to optimize applications
  • Confident experience with AI workloads, with an emphasis on inference workloads
  • Ability to work independently with a remote team with minimal direction

Nice to have

  • Experience with on-prem infrastructure architecture and large-scale cloud deployments
  • Experience with cloud native tooling including Terraform, Kubernetes, Helm
  • Background in building large scale infrastructure that deliver workloads via containers
  • Experience optimizing and troubleshooting performance of compute infrastructure
  • Deploying AI agents to increase productivity and accelerate content delivery
  • Critical thinking capabilities that leverage fundamentals to deduce solutions to unforeseen problems

What the JD emphasized

  • 15+ years of meaningful work experience
  • AI workloads, with an emphasis on inference workloads

Other signals

  • AI inference at scale
  • physical AI through digital simulation
  • AI factory journey
  • inference use cases
  • hybrid cloud architectures
  • AI workloads, with an emphasis on inference workloads