Job description

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, cost, TCO, and operational complexity. • Understand design patterns, fundamental business logic, component-based architecture, and evolutionary architecture. • Build and detail comprehensive API strategies, middleware integrations, and orchestration workflows to ensure seamless communication across distributed enterprise software. • Integrate with non-cloud technologies and third-party vendor products/services. What we need to see: • Bachelor's degree or equivalent experience. • 12+ years of software or infrastructure architecture experience. • 3+ years of experience with micro-services architectures. • Experience with system architecture, performance, and networking specifically developing and deploying distributed solutions. • Proven experience designing, building, or maintaining complex AI, HPC, or cloud-native infrastructure from rack-scale systems through full data center deployments. • Proven expertise in crafting and deploying complete software platforms spanning edge, on-premises, and cloud environments. • Strong understanding of GPU-accelerated systems, high-density servers, PCIe, NVLink, CPU/GPU platform design, rack integration, power, cooling, mechanical constraints, and data center deployment realities. • Deep networking knowledge across Ethernet, InfiniBand, RDMA, RoCE, routing, switching, congestion control, network segmentation, and high-performance cluster fabrics. • Deep proficiency in modern integration patterns, event-driven architectures (e.g., Kafka, RabbitMQ), and container orchestration (e.g., Kubernetes, Docker). • Strong grasp of cloud-native systems with emphasis on high availability, scalability, and security in compute environments. Ways to stand out from the crowd: • Ability to work optimally with NVIDIA and its partners to deliver prescriptive, validated, and scalable enterprise AI factory architectures that reduce deployment complexity and accelerate time to value. • Ability to connect product vision, customer feedback, and deep system architecture to develop practical designs that enterprises can deploy, operate, and expand in production. NVIDIA is widely considered one of the technology world’s most desirable employers. We have some of the world's most forward-thinking and hardworking people on our team. 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 208,000 USD - 327,750 USD for Level 5, and 240,000 USD - 379,500 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until June 2, 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.

Requirements

Must-haves

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, cost, TCO, and operational complexity.
Understand design patterns, fundamental business logic, component-based architecture, and evolutionary architecture.
Build and detail comprehensive API strategies, middleware integrations, and orchestration workflows to ensure seamless communication across distributed enterprise software.
Integrate with non-cloud technologies and third-party vendor products/services.
Bachelor's degree or equivalent experience.
12+ years of software or infrastructure architecture experience.
3+ years of experience with micro-services architectures.
Experience with system architecture, performance, and networking specifically developing and deploying distributed solutions.
Proven experience designing, building, or maintaining complex AI, HPC, or cloud-native infrastructure from rack-scale systems through full data center deployments.
Proven expertise in crafting and deploying complete software platforms spanning edge, on-premises, and cloud environments.
Strong understanding of GPU-accelerated systems, high-density servers, PCIe, NVLink, CPU/GPU platform design, rack integration, power, cooling, mechanical constraints, and data center deployment realities.
Deep networking knowledge across Ethernet, InfiniBand, RDMA, RoCE, routing, switching, congestion control, network segmentation, and high-performance cluster fabrics.
Deep proficiency in modern integration patterns, event-driven architectures (e.g., Kafka, RabbitMQ), and container orchestration (e.g., Kubernetes, Docker).
Strong grasp of cloud-native systems with emphasis on high availability, scalability, and security in compute environments.
Ability to work optimally with NVIDIA and its partners to deliver prescriptive, validated, and scalable enterprise AI factory architectures that reduce deployment complexity and accelerate time to value.
Ability to connect product vision, customer feedback, and deep system architecture to develop practical designs that enterprises can deploy, operate, and expand in production.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until June 2, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

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Keywords to mirror

aikubernetesmlapidocker

Platform: eightfold
Effort: medium

Benefits

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