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Job Summary:
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years, and they are seeking a Senior Product Architect for their Storage team. The role involves architecting end-to-end reference architectures for AI workloads and collaborating with partners to optimize storage infrastructure for modern AI deployments.
Responsibilities:
• Architect end-to-end reference architectures for disaggregated inference (aligned with NVIDIA Dynamo), large-scale foundation model training, and agentic AI pipelines — co-developed with storage and ecosystem partners.
• Design and validate storage-optimized AI infrastructure, including KV Cache tiering strategies, checkpoint acceleration, and high-throughput dataset pipelines that leverage RDMA and NVMeoF fabrics.
• Define system-level architectures spanning Rubin graphics processors, Vera central processing units, BlueField data processing units, NVLink interconnects, and Spectrum-X Ethernet to improve efficiency across the full 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.
• Leverage 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 collaborators in the ecosystem to co-innovate, deliver proof-of-concepts (POCs) and MVPs that demonstrate end-to-end AI platform performance leadership.
Qualifications:
Required:
• 12+ years of experience architecting datacenter-scale AI, HPC, or storage infrastructure as a Principal Architect, Solutions Architect, Principal Engineer, or equivalent.
• Bachelors in Computer Science or related field (or equivalent experience).
• Deep expertise in AI infrastructure build, including disaggregated inference architectures, LLM training pipelines, and autonomous AI system patterns.
• Hands-on experience with RDMA (RoCEv2/InfiniBand), high-performance storage protocols (NVMeoF, GPFS, Lustre, or S3-compatible object storage), and low-latency fabric design.
• Strong understanding of KV Cache management strategies, including tiered memory/storage hierarchies for inference optimization.
• Familiarity with Retrieval-Augmented Generation (RAG) architectures and the storage, indexing, and retrieval patterns they demand at scale.
• Experience with NVIDIA DOCA or equivalent DPU/SmartNIC programming frameworks for offloading data plane and storage services.
• Proven foundation in networking: Spectrum-X Ethernet, InfiniBand, NVLink Switch fabrics, congestion control, and datacenter topologies.
Preferred:
• Proven experience designing reference architectures jointly with storage or infrastructure OEM partners (e.g., NetApp, DDN, VAST, Pure Storage, Dell or similar).
• 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 upcoming Vera-Rubin platforms and their system-level implications for AI workloads.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.