Senior Solution Architect, AI Infrastructure

Remote from: USA
Salary, yearly, USD: 184,000 - 356,500
Department: Software Engineering
Employment type: Full Time,
Job posted: 11 May 2026
Apply before: 11 Jun 2026
Experience level: Senior
Views / Applies: 235 / 32

About company

About NVIDIA

NVIDIA is a leader in AI computing and graphics technology.

Computer Hardware
1993

Actively Hiring

AI Summary

NVIDIA's Federal business unit seeks a Senior Solution Architect for AI Infrastructure to lead the design and deployment of large-scale GPU systems for US government clients. The role involves working with cloud partners and OEMs, guiding customers on network and compute/storage design, and debugging cluster performance. Ideal candidates have 6+ years in solution engineering, expertise in HPC or networking, and strong customer-facing skills. This position requires US citizenship and offers the opportunity to drive AI transformation in the public sector.

Job Complexity

Easy Hard

AI Insight The role demands deep technical expertise in GPU infrastructure, networking, and AI, combined with customer-facing and cross-functional leadership skills, making it highly challenging.

Salary Analysis

AI Insight The offered salary range of $184,000-$356,500 (median $270,250) is competitive for a Senior Solution Architect role in AI infrastructure, aligning with top-tier tech companies. The market range for this role is typically $150,000-$350,000, so the offer is attractive.

Key Skills

Accelerated Computing AI Infrastructure GPU Clusters High-Performance Computing InfiniBand Solution Architecture Customer Engagement Network Design Deep Learning US Federal Government

Cover Letter Sample

I am excited to apply for the Senior Solution Architect, AI Infrastructure position at NVIDIA's Federal business unit. With over 6 years of experience in solution engineering and a deep background in accelerated computing and AI, I am well-prepared to drive digital transformation for US government clients. My expertise in GPU infrastructure, high-performance networking, and customer engagement aligns perfectly with the requirements outlined in the job description.

In my previous role, I successfully led the design and deployment of large-scale GPU clusters for federal customers, optimizing network performance and ensuring seamless integration. I have a proven track record of collaborating with cross-functional teams to deliver complex solutions and have extensive experience with NVIDIA technologies, including GPUs, InfiniBand, and cluster management tools.

I am particularly drawn to this opportunity because of NVIDIA's leadership in AI and my passion for serving the public sector. I am confident that my technical skills and customer-focused approach will enable me to excel as a trusted advisor to your clients. I look forward to the possibility of contributing to NVIDIA's mission and would welcome the chance to discuss my qualifications further.

Possible Interview Questions

Can you describe a time when you led the deployment of a large-scale GPU cluster for a customer? What challenges did you face and how did you overcome them?

In my previous role, I led the deployment of a 1000-GPU cluster for a federal research lab. Key challenges included network congestion and cooling issues. I worked with the networking team to optimize InfiniBand topology and implemented liquid cooling solutions, resulting in a 20% performance improvement.

How would you approach a customer who is skeptical about adopting AI and GPU infrastructure?

I would start by understanding their specific pain points and use cases, then present case studies and ROI analyses from similar organizations. I would also offer a proof-of-concept project to demonstrate tangible benefits, such as reduced training times or improved model accuracy.

Explain the impact of network architecture on GPU cluster performance. How do you optimize it?

Network architecture directly affects data transfer speeds and latency, which are critical for distributed training. To optimize, I ensure low-latency interconnects like InfiniBand, use NCCL for efficient communication, and design a non-blocking topology to avoid bottlenecks.

Describe your experience with NVIDIA's software stack, including NCCL, DCGM, and UFM. How have you used them in production?

I have used NCCL to optimize multi-GPU communication in training workflows, DCGM for monitoring GPU health and performance, and UFM for fabric management in InfiniBand networks. In one project, I used DCGM to identify a memory leak in a GPU application, reducing downtime by 30%.

As a solution architect, how do you balance customer requirements with product capabilities? Give an example.

When a customer requested a feature that wasn't in the product roadmap, I facilitated a workshop to understand their underlying need. We discovered a workaround using existing APIs that met their requirements. I then provided feedback to the product team, which later incorporated the feature based on customer demand.

NVIDIA’s Federal business unit is seeking an experienced solutions lead. This person will be passionate about crafting an entire market and serving the US Federal Government during digital transformation. The ideal candidate will have a strong technical background in accelerated computing technology and artificial intelligence and leverage those skills to help government programs within the US Public Sector market. They will collaborate closely with product, engineering, and federal customers to accelerate NVIDIA technology in the design to deployment of large-scale GPU infrastructure. A successful candidate will demonstrate skill in transcending boundaries, working effectively with product teams, account managers, field organization, and customers to drive success.

You must be a U.S. Citizen to apply for this position.

What you’ll be doing:

Working with NVIDIA Cloud Partners and OEMs in Public Sector on large data center GPU server and networking system deployments. Guide customer discussions on network design, compute/storage, and support bring up of server/network/cluster deployments. You will need to visit customer data center during bring up phase.
Become the primary technical driver for customers during the design, development, construction, integration, and production of GPU infrastructure and applications throughout the entire customer lifecycle.
Work as the customer’s trusted advisor conducting regular technical customer meetings for product roadmap, cluster issue debugging, feature discussions and introduction to new technology solutions.
Partner with other SAs, Account Managers, Engineering, Product, and business leaders to align on strategies, assess technical needs, and secure business opportunities for NVIDIA.
Analyze and debug compute/network configuration and performance issues to deliver performant clusters.
Prepare and deliver technical content to customers including presentations, workshops, reference architectures, tutorials, publications.
Educate C-Suite-level decision-makers about the benefits of AI and high-performance computing.
Lead communication with customers and NVIDIA Management.
Provide constructive feedback to engineering and product regarding product requirements, customer experience, documentation, and tools.
Ability to travel ~20%

What we need to see:

The position requires solving complex multidisciplinary problems. They will often be responsible for leading the resolution of technical issues across multiple engineering teams and coordinating the solutions to the customer.

BS/MS/PhD in Electrical Engineering, Computer Science or equivalent experience.
6+ years supporting Solution Engineering (or similar Sales Engineering, Cloud Engineering, Solution Architecture) including experience working directly with partners and customers.
Experience with high performance Networking or CPU/GPU application acceleration is preferred.
Strong interpersonal skills and a background in direct customer interaction.
Subject Matter Expertise (SME) in High-Performance Computing, or Networking
Critical thinking capability, the ability to concisely communicate vision (both written and verbal) and engage in cross-functional collaboration.

Ways to stand out from the crowd:

Familiarity with NVIDIA GPUs, NVIDIA Networking technologies (e.g. NICs, RoCE, InfiniBand), and systems technology such as NCCL, DCGM, UFM, Mission Control, and Base Command Manager. Experience building and/or integration artificial intelligence solutions.
Experience with bring up and deployment of large GPU clusters, including deploying and optimizing high-speed networks (InfiniBand/Ethernet), with a clear understanding of how network architecture impacts GPU cluster performance.
Experience working with enterprise developers and strong customer-facing skills.
Active Security Clearance is highly desirable.

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, independent, and focused on serving the mission of the U.S. Federal Government, 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 184,000 USD – 287,500 USD for Level 4, and 224,000 USD – 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 15, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

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