Solutions Architect, Supercomputing

NVIDIA NVIDIA · Semiconductors · TX +2 · Remote

Solutions Architect role focused on engaging with customers and partners to support applications and platforms leveraging NVIDIA technology in HPC, ML, AI Physics, Foundation Modeling, and Agentic AI. Requires technical expertise, communication skills, and experience with modern AI architectures.

What you'd actually do

  1. Partner with our industry and account teams in a customer facing role to develop a keen understanding of customer goals, strategies, and technical needs as well as help to define and deliver high-value solutions meeting these needs.
  2. Document what you know and teach others. This can vary from building targeted samples, to writing white papers, blogs, and wiki articles, to simply working through hard problems with a customer on a whiteboard.
  3. Be an industry leader with vision on integrating NVIDIA technology into AI Workloads and Workflows, HPC, and enterprise GPU and networking architectures for advanced applications both in the datacenter and at the edge.
  4. Strategically partner with lighthouse customers and industry-specific solution partners targeting our computing platform.

Skills

Required

  • 5+ years of work-related experience in data science or software development with knowledge of parallel computing with GPUs.
  • Background working with modern application deployment practices including but not limited to Slurm, Docker/Containers, and Kubernetes.
  • Experience with modern Generative AI and Agentic AI architecture and frameworks.
  • Strong written and oral communication skills with the ability to effectively collaborate with accounts, customers, management, and engineering.
  • Experience supporting customers/partners in technical engagements.
  • Strong organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very complex projects.
  • Strong analytical and problem-solving skills.

Nice to have

  • Experience applying data science to industry problems.
  • Experience using GPGPU programming and design practices.
  • CUDA programming and optimization experience.
  • Background with network software development.
  • Experience with AI: Published record of thought leadership in a technical area or industry segment - Deep Neural Network, Machine Learning R&D - Agentic AI, surrogate Models, or foundation models.

What the JD emphasized

  • security clearance
  • U.S. citizenship

Other signals

  • customer facing role
  • technical advisor
  • integrating NVIDIA technology into AI Workloads and Workflows