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Senior Solutions Architect - AI Infrastructure

NVIDIA•Canada, United States•🌍 Remote
Full-timeSenior
$184K - $357K
per year
👁️ 0 views•📝 0 applications•Posted 10/28/2026•Expires 12/27/2026
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Job Description

NVIDIA is building the world’s most groundbreaking and innovative accelerated computing platforms for AI and HPC. Because of our work, scientists, researchers, and engineers can push the boundaries of what’s possible.

We pioneered a supercharged form of computing that powers everything from breakthrough AI research to the world’s fastest supercomputers. We are seeking a highly motivatedSenior Solutions Architectto join the NVIDIA Cloud Partners team with a focus on GPU, NVLink, and infrastructure design.

In this role, you will be at the forefront of assisting with designs and architectures for some for the largest next-generation GPU-based clusters enabling the world’s most advanced AI supercomputers and enterprise AI infrastructure in the field.

As a Solutions Architect, you will serve as a key technical expert bridging NVIDIA ’s ground breaking GPU and NVLink technology designs as well as all of our software solutions directly between engineering and field teams supporting customers with the most demanding requirements.

You will work on end-to-end cluster design and architecture, performance modeling, validation, and NPI cluster deployments. Your expertise will directly influence how the world’s leading AI companies, cloud providers, hyperscalers, research institutions, and enterprises build their infrastructure.

What you’ll be doing: Partner with NVIDIA Cloud Partners in GPU cluster design and networking and convey architecture and optimal process information for building next-generation architectures.

Guide NVIDIA Cloud Partnersin cluster design, weighing design principles but also complex, situational limitations to make the most performant and supportable GPU clusters possible.

Work closely with NVIDIA Cloud Partnersto ensure successful first deployments with new products, including new network architectures and topologies. Feedback customer/field perspectives on cluster design and workflows back to engineering teams designing internal clusters. Perform hands-

Required Skills

GPUNVLinkinfrastructure designcluster designperformance modelingvalidationNPI cluster deploymentsnetwork architecturestopologiesAIHPCcloud infrastructureengineering collaborationcustomer support

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