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NVIDIA

Infrastructure Solutions Architect - OEM

  • Office
  • 6+ years

Salary

$152,000 - 241,500/ year

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Description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

We are looking for an Infrastructure Solutions Architect to help revolutionize computing. At NVIDIA, we encourage an inclusive and collaborative environment where ambitious individuals can grow. Our dedication to innovation and excellence has made us a leader in technology. We are now seeking outstanding talent to join us on this journey.

What you’ll be doing:

Serve as the senior technical point of contact for OEM Federal deployments of NVIDIA GPU-accelerated platforms, including PCIe GPUs, HGX, and MGX systems, addressing any blocking issues.

Own Issues End to End: Take responsibility for customer issues from start to finish — prioritizing platform, firmware, and workload problems. Drive these issues through the OEM's support tiers into NVIDIA engineering with the necessary logs and reproduction details to identify the root cause. Follow through with the customer until resolution.

Failure Analysis & RMA: Establish and complete diagnostic, RMA eligibility, and replacement procedures for Federal deployments. This includes situations where failed hardware and logs must remain on-site at the customer facility.

Navigate Federal security frameworks including FedRAMP, IL5/IL6, and air-gapped (SCIF) environments, and help the customer meet sanitization and chain-of-custody requirements for hardware returns.

Partner with OEM Federal support and services teams to reduce blocking issues and unnecessary dispatches. Detail failure signatures to build the Federal knowledge base and apply AI tools where the environment allows.

What we need to see:

Due to the classified nature of the work, the selected candidate must be a U.S. citizen and possess and maintain an active U.S. Government TS/SCI clearance. Certain Intelligence Community customer assignments may also require a current U.S. Government-administered Counterintelligence Scope or Full Scope Polygraph.

BS or MS in Computer Engineering, Electrical Engineering, Computer Science, or equivalent experience

5+ years of engineering experience on multi-GPU platforms, including at least 3 years in a customer-facing support, field engineering, or blocking issue role.

Strong system software expertise across firmware, BIOS, kernel, drivers, and operating systems, with the ability to troubleshoot, optimize, and customize Linux environments for AI/ML workloads.

Expert knowledge of data center infrastructure — x86/ARM systems, high-performance storage, and low-latency networking (InfiniBand/RDMA).

Professional-level communication and organizational skills, including adjusting to the technical level of the audience, staying calm and focused in negative situations, and driving issues through to closure.

This role requires up to 35% travel to customer, partner, and data center sites, including secure facilities, and occasional weekend and holiday coverage.

Ways to stand out from the crowd:

Dell Ecosystem Expertise: Proven experience with Dell PowerEdge GPU servers and Dell's management software (OpenManage, APEX), and familiarity with Dell's support and process for handling blocking issues.

Federal Mission Experience: Direct experience supporting DoD, Intelligence Community, or Civilian agency deployments, and comfort operating within their security and logistics constraints.

Programming Depth: Proficiency in Python for building custom diagnostic and analysis tooling, and C/C++ for platform OS, firmware, and driver work.

Cluster & HPC Technologies: Containerized and scheduled environments (Docker, Kubernetes, Slurm) and upper layer protocols such as NCCL and MPI.

Performance Analysis: Experience analyzing performance of distributed GPU-accelerated workloads.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, results-oriented and enjoy learning while having fun, then what are you waiting for? Apply today!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

Responsibilities

  • Applications for this job will be accepted at least until September 21, 2026.
  • This posting is for an existing vacancy.
  • NVIDIA uses AI tools in its recruiting processes.
  • NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Where you’d work

From the office

You can work from

  • United States

No visa sponsorship

About the company

NVIDIA

Also hiring in United States, Munich, Germany, France and 14 more places

273 of their 660 open roles are remote

Your chances

Worth a look before you spend an evening tailoring a CV for it.

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1 red flag

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  • Must-haves
Details12 facts · Role, Location, Compensation, Employment
Tech stack
  • Python
  • Kubernetes
  • Docker
  • Linux
Type
Full-time
Equity
Equity offered
Specialty
Solutions Engineering
Region
United States
Pay period
Annual
Show 6 more factsShow less

Role

Category
Solutions & Support
Specialty
Solutions Engineering
Experience
25+ years
Tech stack
  • Python
  • Kubernetes
  • Docker
  • Linux

Location

Work model
Office
Region
United States
Remote from
  • United States
Visa sponsorship
Not sponsored

Compensation

Salary
$152,000 - 241,500 / year
Pay period
Annual
Equity
Equity offered

Employment

Type
Full-time

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