NVIDIA

NVIDIA

Posted via Workday

Manager, Solutions Architecture - Emerging AI labs

Posted Aug 11, 2026

Role at a glance

Salary
$224K – $356.5K/yr
Location
4 Locations, California, United States
Work arrangement
On-site
Employment
Full-time
Experience
8+ overall years in Systems/Solutions/Field Engineering, Network or Data Center Engineering, or similar roles, with 2+ years leading or...
Education
BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.

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Role Summary

AI-generated

NVIDIA is seeking a Solutions Architect Manager to lead a team of GPU, networking, and software solution architects and engineers. The role supports end-to-end deployment of AI hardware and software technologies for strategic AI-native customers and emerging AI labs, while contributing to solution design, debugging, and product roadmap feedback.

What You'll Do

  • Recruit, manage, prioritize, and mentor a team supporting large-scale GPU and AI networking deployments.
  • Lead technical reviews, design decisions, and critical compute and network debugging efforts.
  • Guide compute, network, and software architecture discussions and support server, network, and cluster bring-up, including on-site data...
  • Collect and synthesize customer-specific requirements across projects.
  • Partner with GPU and Network Systems Engineering, Product Management, and Sales to influence roadmap priorities and reference designs.
  • Expand NVIDIA’s solution engagements across strategic AI-lab customers.

Generated from the employer's posting. Verify important details before applying.

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Qualifications

System-level expertise across CPU/GPU server architecture, NICs, Linux, system software, kernel drivers, and data center networking including Ethernet and/or InfiniBand. Proven ability to lead technical teams, set priorities, drive complex projects from design through production, and work with Product Management, Sales, and Engineering. Excellent written and verbal communication, time management, and direct people management and recruiting experience for geographically distributed technical teams.

Required

  • CPU/GPU server architecture
  • NICs
  • Linux
  • System software
  • Kernel drivers
  • Ethernet and/or InfiniBand networking
  • Data center networking tooling
  • Cluster performance troubleshooting

Preferred

  • Large cluster or supercomputing environment bring-up and deployment
  • AI lab or frontier-model infrastructure deployments
  • Customer-facing field engineering or pre/post-sales architecture
  • C/C++
  • Linux kernel
  • NVIDIA GPU systems and SDKs such as CUDA
  • NVIDIA networking technologies including NICs, RoCE, and InfiniBand
  • ARM-based CPU solutions

Original job description

Content provided by the employer

NVIDIA is looking for a hands-on Solutions Architect Manager to lead a team of GPU, networking & software solution architects and engineers. Do you want to build and lead a group that designs, debugs, and deploys new AI hardware and software technologies into production in customer data centers? As part of the NVIDIA SA organization, you will drive people and technical leadership for end-to-end solutions deployments at some of NVIDIA's most strategic AI-native customers and emerging AI labs, while directly contributing to solution design and deep-dive debugging and product roadmap shaping through customer feedback.
 

What you will be doing:

  • Recruit & manage a team of solutions architects, system/network and software engineers focused on large-scale GPU and AI networking deployments for emerging AI labs. Set priorities, allocate resources, mentor, and ensure high-quality customer delivery across multiple concurrent projects - while remaining directly involved in key technical reviews, design decisions, and critical debug efforts.

  • Provide deep subject-matter expertise in advanced GPU and network systems and serve as the senior technical point of contact for strategic AI-native customers and emerging AI labs. Personally lead and guide complex compute and network configuration and performance debugging, working side-by-side with your team to deliver performant, reliable clusters.

  • Guide your team as they lead compute, network, and software architecture discussions, and support server, network, and cluster bring-up, including on-site data center work where needed.

  • Systematically collect and synthesize customer-specific requirements across your portfolio. Partner with GPU and Network Systems Engineering, Product Management, and Sales to influence roadmap priorities and packaging of reference designs and solutions.

  • Seek opportunities to expand NVIDIA's solution engagements across strategic AI-lab customers.

What we need to see:

  • BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.

  • 8+ overall years in Systems/Solutions/Field Engineering, Network or Data Center Engineering, or similar roles, with 2+ years leading or mentoring engineers or architects (formal manager or strong tech lead).

  • System-level expertise across CPU/GPU server architecture, NICs, Linux, system software, and kernel drivers. Experience with data center networking including Ethernet and/or InfiniBand switches, NICs, fabrics, associated tooling, and cluster performance troubleshooting. Familiarity with data center infrastructure (power, cooling, deployment constraints).

  • Proven ability to lead technical teams, set priorities, and drive complex projects from design through production. Demonstrated success working with Product Management, Sales, and Engineering.

  • Strong time management skills and ability to balance planning with hands-on support where needed.

  • Excellent written and verbal communication, including the ability to lead customer meetings, communicate status and risks, and produce clear design docs, debug summaries, and presentations.

  • Direct people management & recruiting experience for geographically distributed technical teams.

Ways to stand out from the crowd:

  • Track record leading bring-up and deployment of large clusters or supercomputing environments.

  • Background working with fast-moving AI labs or frontier-model infrastructure deployments and customer-facing roles (field engineering, or pre/post-sales architecture).

  • Systems engineering, coding, and debugging skills including experience with C/C++, Linux kernel, and drivers.

  • Hands-on experience with NVIDIA GPU systems and SDKs (e.g., CUDA), NVIDIA networking technologies (NICs, RoCE, InfiniBand), and/or ARM-based CPU solutions.

  • Familiarity with virtualization and cloud-native networking concepts.


We make extensive use of conferencing tools, but occasional travel (up to 20%) is required for on-site customer visits and industry events. We are open to remote work locations and look forward to have you join our team!

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 and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 14, 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.

NVIDIA

About the company

NVIDIA

Large Enterprise

NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.