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Senior System Architect, Enterprise Reference Architectures

NVIDIA · Santa Clara, United States

Information Technology Infrastructure & Support Hybrid Full-time Posted 5 days ago

About this role

NVIDIA Enterprise Platforms Group is seeking a Senior System Architect to define, design, and validate enterprise AI factory reference architectures. This role sits at the intersection of product strategy, system architecture, customer requirements, and hands-on infrastructure validation, helping turn NVIDIA accelerated computing, networking, storage, and AI software into repeatable blueprints that enterprises and partners can deploy with confidence. The ideal candidate brings deep data center architecture experience, strong product and customer instincts, and practical proficiency across accelerated compute, high-performance networking, storage, Kubernetes, observability, automation, and AI/ML operations

This person can translate ambiguous customer and partner needs into clear requirements, architecture patterns, validation plans, and field-ready technical mentorship! What you'll be doing: Define and drive full-stack enterprise AI factory baseline architectures across compute, networking, storage, virtualization, orchestration, security, observability, and NVIDIA AI software to deliver on-prem cloud native-platform and cluster reference builds. Architect reference builds for end-to-end software systems and platforms based on scalable, portable, and resilient builds and drive evaluation of different platforms, capture information on differences in implementations, and conduct research on the platform behavior under different workloads. Work with Product Management, Product Architects, Engineering, Solution Architecture, Program Management, and field teams to develop product direction, architecture requirements, roadmap inputs, and execution plans Develop and validate scalable cluster designs for enterprise AI/ML systems, including on-premises and hybrid-cloud deployments optimized for training, fine-tuning, inference, agentic AI, physical AI, and HPC workloads Evaluate tradeoffs across performance, scalability, resiliency, manageability, security, power, cooling, c

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