NVIDIA
AI
SolutionsArchitect,Networking
Neural analysis suggests this role is
optimal for Senior candidates.
“Solutions Architect, Networking at NVIDIA. Skills: Networking Solutions Architecture, AI Infrastructure, High-Performance Networking, NVIDIA GPU and Networking Platforms, Distributed Systems. design and deploy large-scale AI Factories across Canada. collaborate with customers to build end-to-end infrastructure”
What You'll Achieve.
rapidly bring NVIDIA Data Center GPU and networking platforms to market at scale; build, deploy, and optimize large-scale AI training and inference infrastructure using NVIDIA technology; taking GPU or infrastructure products from pilot to high‑volume deployment in large data center environments
Industry & Context.
Solve challenging technical problems involving GPUs, networking, drivers, containers, firmware, and distributed system interactions; Ability to identify performance bottlenecks at the cluster, node, accelerator, network, or application layer; Demonstrated leadership resolving multi‑team infrastructure challenges across engineering, product, and customer groups
Some travel to customer sites is required, up to 20%, occasional travel is required for on-site visit to customers and industry events
What They're Looking For.
Must Have
5+ years of Solution Architecture (or similar Sales Engineering, Systems Engineering, Cloud Engineering, Solution Engineering), Understanding of high‑performance networking technologies (e. g. , RDMA, congestion control, high‑bandwidth interconnects), and their role in distributed AI workloads, Hands‑on experience with bring‑up and validation of large‑scale NVIDIA GPU platforms, including multi‑GPU and multi‑node architectures, Familiarity with NVIDIA system software stacks: CUDA, NCCL, NVSwitch/NVLink, driver behavior, and performance tuning, Ability to identify performance bottlenecks at the cluster, node, accelerator, network, or application layer, Linux fundamentals across drivers, kernel subsystems, cgroups, containers, and node‑level performance analysis, Excellent presentation, communication, and collaboration skills
Nice to Have
Prior experience deploying or optimizing deep learning training and inference at scale in production environments on large GPU clusters, Familiarity with NVIDIA hardware (such as GPUs, networking, storage) and systems technology such as NCCL, DCGM, UFM, Mission Control, Base Command Manager, Demonstrated leadership resolving multi‑team infrastructure challenges across engineering, product, and customer groups, A consistent record of taking GPU or infrastructure products from pilot to high‑volume deployment in large data center environments
What You'll Do.
design and deploy large-scale AI Factories across Canada
collaborate with customers to build end-to-end infrastructure
become a trusted technical advisor
work on exciting projects
focused on how high-performance networking enables generative AI
large language models
and production AI inference pipelines
collaborate with a diverse set of internal engineering
and business teams on performance analysis and modeling of these large GPU clusters
Becoming the trusted technical advisor for NVIDIA Cloud Partners in Canada to rapidly bring NVIDIA Data Center GPU and networking platforms to market at scale
Collaborating directly with customers to build
and optimize large-scale AI training and inference infrastructure using NVIDIA technology
Analyzing deployment and performance data
identifying product health trends
and operational risks
Solve challenging technical problems involving GPUs
and distributed system interactions
Deliver streamlined executive‑level communication on status
and required decisions
How You'll Work.
Team & Collaboration
collaborate with customers; collaborate with a diverse set of internal engineering, product, and business teams; Demonstrated leadership resolving multi‑team infrastructure challenges across engineering, product, and customer groups
Communication Scope
Deliver streamlined executive‑level communication on status, risks, progress, and required decisions; Excellent presentation, communication, and collaboration skills
Full Job Description
NVIDIA is seeking outstanding Networking Solutions Architects (SA) to help design and deploy large-scale AI Factories across Canada. In this role, you will collaborate with customers to build end-to-end infrastructure. You will become a trusted technical advisor working on exciting projects, focused on how high-performance networking enables generative AI, large language models, and production AI inference pipelines. You will also collaborate with a diverse set of internal engineering, product, and business teams on performance analysis and modeling of these large GPU clusters. You should be comfortable working in a dynamic environment and have hands-on experience with NVIDIA networking and GPU technologies. This is an excellent opportunity to be at the center of Canada's rapidly growing AI infrastructure landscape. **What You Will Be Doing:** * Becoming the trusted technical advisor for NVIDIA Cloud Partners in Canada to rapidly bring NVIDIA Data Center GPU and networking platforms to market at scale. * Collaborating directly with customers to build, deploy, and optimize large-scale AI training and inference infrastructure using NVIDIA technology. * Analyzing deployment and performance data, identifying product health trends, system bottlenecks, and operational risks. * Solve challenging technical problems involving GPUs, networking, drivers, containers, firmware, and distributed system interactions. * Deliver streamlined executive‑level communication on status, risks, progress, and required decisions. * Some travel to customer sites is required, up to 20%. **What We Need To See:** * BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) * 5+ years of Solution Architecture (or similar Sales Engineering, Systems Engineering, Cloud Engineering, Solution Engineering). * Understanding of high‑performance networking technologies (e.g., RDMA, congestion control, high‑bandwi
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