Solutions Architect, Ai Infrastructure

NVIDIA

Base: 184,000 usd - 287,500 usd (level 4); 224,000...
Not specified
Data center gpu server and networking infrastructure
Network topologies, compute/storage
Server/network/cluster deployments
NVIDIA is seeking an experienced Solutions Architect for AI Infrastructure to lead the deployment of innovative AI solutions. The ideal candidate will have a strong background in solution engineering, networking, and data center infrastructures, along with excellent communication skills

Job Summary

  • Lead the charge in deploying innovative AI solutions with a world-class team pushing the boundaries of AI and accelerated computing.
  • Work with NVIDIA AI Native customers on data center GPU server and networking infrastructure deployments, guiding discussions and supporting bring-up.
  • Conduct regular technical meetings as a trusted advisor, discussing roadmaps, debugging, and new technology introductions, while building custom demos and proofs of concept.

Matching Summary

Match Score: 85

NVIDIA is seeking an experienced Solutions Architect for AI Infrastructure to lead the deployment of innovative AI solutions. The ideal candidate will have a strong background in solution engineering, networking, and data center infrastructures, along with excellent communication skills.

Salary

Base: 184,000 USD - 287,500 USD (Level 4); 224,000 USD - 356,500 USD (Level 5); Equity: eligible; Benefits: eligible

Skills & Requirements

Must-have

  • Data center GPU server and networking infrastructure
  • Network topologies, compute/storage
  • Server/network/cluster deployments
  • Technical meetings with customers
  • Custom demonstrations and proofs of concept
  • Compute/network performance issues analysis

Nice-to-have

  • External customer-facing skills
  • Large cluster bring-up and deployment
  • Virtualization technology concepts familiarity

Key Requirements

  • BS/MS/PhD or equivalent experience
  • 7+ years in Solution Engineering
  • System-level understanding of server architecture
  • Practical knowledge of networking
  • Familiarity with DevOps/MLOps technologies
  • Effective time management and ability to balance multiple tasks
  • Excellent communication skills

Work Rights

Not specified

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