Senior AI Factory Solutions Architect - Equity Eligible

NVIDIA

New Jersey

On-site

USD 184,000 - 357,000

Full time

8 days ago
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Benefits offered by this job

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Benefits

Job summary

NVIDIA seeks a highly technical Solution Architect to act as a forward‑deployed liaison among NVIDIA’s Partner Network, internal teams, and enterprise customers. You will support planning, development, and deployment of large-scale AI factories based on NVIDIA reference designs, mentoring partners and accelerating adoption.

You will embed with customer teams to bridge solution development, implementation, and post‑deployment optimization, ensuring reliability, scalability and cost‑effectiveness

Qualifications

  • Bachelor's degree or equivalent experience in Engineering or related field.
  • Expert with infrastructure delivery in hyperscale data centers.
  • 8+ years of experience in AI/HPC data centers preferred.

Responsibilities

  • Plan AI Factory deployments with NVIDIA teams and partners.
  • Build processes, relationships and workflows to deploy at speed.
  • Review installation plans and BOMs for alignment with reference architectures.
  • Audit data center hardware readiness and pre deployment risks.
  • Implement QA processes to meet specs and performance benchmarks.
  • Create partner playbooks, deployment guides and runbooks.
  • Mentor partners on deploying NVIDIA AI factory solutions.
  • Represent feedback to NVIDIA product and engineering teams.

Skills

Hyperscale DCs
DC operations
Project planning
Travel readiness
Executive communication
Partner enablement

Education

Bachelor's degree in Engineering

Job description

NVIDIA seeks a highly technical Solution Architect to act as a forward‑deployed liaison among NVIDIA’s Partner Network, internal teams, and enterprise customers. You will support planning, development, and deployment of large-scale AI factories based on NVIDIA reference designs, mentoring partners and accelerating adoption.

You will embed with customer teams to bridge solution development, implementation, and post‑deployment optimization, ensuring reliability, scalability and cost‑effectiveness

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