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NVIDIA

Designs the chips and software that power AI

Senior Solutions Architect - AI Infrastructure Build Readiness, Execution

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A bachelor's or master's degree, or equivalent experience, in Computer Science, Engineering, or a related field.
  • At least 8 years of professional experience spanning software or hardware engineering, developer relations, technical partnerships, solutions architecture, or product management, including 3–5+ years of direct hands-on experience in AI infrastructure, data center deployment, or large-scale AI/HPC systems.
  • Deep technical expertise in high-performance computing, AI/ML, data center infrastructure, rack-scale AI infrastructure, or large-scale GPU systems, with a track record of driving product integrations and contributing to software and hardware platforms, systems, and libraries.
  • Ability to communicate complex technical ideas clearly to technical and non-technical audiences, from engineers to C-level executives.
  • Experience working with OEM, ODM, system integrator, or deployment partner ecosystems to drive technical field engagement, partner enablement, or platform adoption at scale.
  • Familiarity with NVIDIA GPU, networking, and AI infrastructure platforms, with a track record of driving integrations in large-scale deployment environments.
  • Experience working with services, field engineering, professional services, manufacturing partners, or deployment services teams.
  • Travel up to 50% to support field engagements, partner sites, and deployment activities.

Responsibilities

  • Serve as a trusted advisor by understanding complex or large-scale customer workloads and mapping them to NVIDIA's technology stack to achieve measurable outcomes.
  • Co-design advanced, scalable architectures with OEM and deployment partners, defining technical direction, integration milestones, and deployment plans.
  • Design, validate, and support solutions through hands-on engagement with deep technical topics.
  • Identify gaps between OEM and deployment partner needs and NVIDIA offerings, and communicate insights that shape internal product and engineering priorities.
  • Lead technical engagements, help customers troubleshoot and resolve complex issues, and advocate for their technical needs.
  • Drive technical enablement and platform adoption by helping developers and enterprises integrate NVIDIA SDKs, frameworks, and systems.
  • Partner with engineering and product teams to ensure successful deployment and continuous improvement of NVIDIA solutions.
  • Lead AI Factory build execution engagements with OEM and deployment partners, driving technical readiness, deployment validation, and issue resolution across NVIDIA AI infrastructure build-outs.

Desired Qualifications

  • Hands-on technical expertise and problem-solving ability to describe solution paths for complex challenges.
  • History of enabling customers or partners to successfully adopt NVIDIA technologies and platforms.
  • Technical vision that influences product and engineering decisions and drives production outcomes.
  • Experience with AI Factory, accelerated computing, rack-scale AI infrastructure, or large-scale GPU system deployments.
  • Experience contributing to deployment playbooks, execution frameworks, or readiness programs for large-scale AI infrastructure build-outs.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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