Senior Product Architect, Storage

Details

NVIDIA is transforming accelerated computing and using AI to define the next era of computing. This role will serve as the link between cutting-edge hardware platforms and real-world AI deployments, translating the capabilities of Rubin GPUs, Vera CPUs, BlueField DPUs, NVLink fabric, and Spectrum-X networking into validated, production-ready blueprints. The role will work with storage ecosystem partners to co-develop reference architectures for the NVIDIA AI Data Platform and optimize compute, fabric, memory, and storage for modern AI workloads.

Responsibilities

• Architect end-to-end reference architectures for disaggregated inference aligned with NVIDIA Dynamo, large-scale foundation model training, and agentic AI pipelines in collaboration with storage and ecosystem partners.
• Design and validate storage-optimized AI infrastructure, including KV Cache tiering strategies, checkpoint acceleration, and high-throughput dataset pipelines using RDMA and NVMeoF fabrics.
• Define system-level architectures spanning Rubin GPUs, Vera CPUs, BlueField DPUs, NVLink interconnects, and Spectrum-X Ethernet to improve efficiency across the AI lifecycle.
• Develop and publish reference architectures, whitepapers, and deployment guides for the NVIDIA AI Data Platform and partner-integrated solutions.
• Drive prototyping, benchmarking, and performance validation of AI infrastructure at scale, diagnosing bottlenecks across compute, networking, and storage layers.
• Use NVIDIA DOCA to architect DPU-offloaded data services, including storage acceleration, telemetry, security enforcement, and network virtualization.
• Collaborate with RAG and autonomous AI teams to build retrieval-optimized storage architectures, including vector database integration, low-latency object access patterns, and inference-aware caching.
• Partner with customers and ecosystem collaborators to co-innovate and deliver proof-of-concepts and MVPs demonstrating end-to-end AI platform performance.

Requirements

• 12 or more years of experience architecting datacenter-scale AI, HPC, or storage infrastructure as a Principal Architect, Solutions Architect, Principal Engineer, or equivalent.
• Bachelor's degree in Computer Science or a related field, or equivalent experience.
• Deep expertise in AI infrastructure, including disaggregated inference architectures, LLM training pipelines, and autonomous AI system patterns.
• Hands-on experience with RDMA, including RoCEv2 and InfiniBand; high-performance storage protocols such as NVMeoF, GPFS, Lustre, or S3-compatible object storage; and low-latency fabric design.
• Strong understanding of KV Cache management strategies, including tiered memory and storage hierarchies for inference optimization.
• Familiarity with Retrieval-Augmented Generation architectures and the storage, indexing, and retrieval patterns required at scale.
• Experience with NVIDIA DOCA or equivalent DPU/SmartNIC programming frameworks for offloading data-plane and storage services.
• Proven networking expertise, including Spectrum-X Ethernet, InfiniBand, NVLink Switch fabrics, congestion control, and datacenter topologies.

Preferred Qualifications

• Experience designing reference architectures jointly with storage or infrastructure OEM partners such as NetApp, DDN, VAST, Pure Storage, or Dell.
• Hands-on deployment experience with disaggregated inference systems, including prefill/decode separation, KV Cache offload, and request routing.
• Deep familiarity with NVIDIA Grace-Hopper, Grace-Blackwell, or Vera-Rubin platforms and their system-level implications for AI workloads.

Compensation and Benefits

• Base salary range: USD 224,000–356,500 per year, determined by location, experience, and compensation for similar positions.
• Eligible for equity and benefits.
• Applications accepted at least until March 17, 2026.
• This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes and is committed to an inclusive, equal-opportunity work environment.