Domain Architect (AI Storage)

About the role

The Domain Architect - AI Storage acts as the primary technical authority for the physical and logical lifecycle of high-performance data platforms across diverse client environments, bridging the gap between architectural design and hands-on execution. You will define the "Gold Standard" for storage infrastructure, moving beyond single-array management to architect repeatable, scalable, and automated data fabrics. You will serve as the technical lead for NVIDIA Cloud Provider (NCP) and private enterprise AI cloud deployments, owning the "Storage" in the critical "Compute-Network-Storage" triad. You will operate with a 60/40 split between delivering complex AI infrastructure (60%) and providing Pre-Sales Subject Matter Expertise (40%).

Key responsibilities

• Lead the installation and configuration of high-performance storage clusters using technologies such as WEKA, DDN (Lustre), VAST Data, or Pure Storage

• Optimise storage client configurations on compute nodes, managing kernel modules and mounting parameters to ensure stability at scale

• Implement GPUDirect Storage (GDS) technologies to bypass the CPU and enable direct data paths between NVMe drives and GPU memory

• Deploy and configure Container Storage Interface (CSI) drivers for Kubernetes/Red Hat OpenShift, ensuring persistent storage is dynamically provisioned for AI workloads

• Design storage classes that differentiate between "Scratch" (High Performance) and "Home/Project" (General Purpose) tiers

• Execute synthetic benchmark suites (IOR, FIO, mdtest) to validate throughput and metadata performance against agreed SLAs

• Troubleshoot I/O issues, analysing client-side logs and fabric counters

• Implement automated data tiering strategies to move datasets between Hot (NVMe), Warm (QLC Flash), and Cold (Object/S3/Tape) tiers

• Lead the architectural sizing for storage opportunities and calculate required performance for specific workloads

• Own the Storage Bill of Materials (BoM), ensuring the correct ratio of Storage Servers to Compute Nodes/GPUs

About you

• Expert-level knowledge of Parallel File Systems (WEKA, Lustre, BeeGFS, GPFS)

• Deep understanding of Object Storage (S3 protocols) for model checkpointing and archiving

• Mastery of storage protocols: NVMe-over-Fabrics (NVMe-oF), NFS over RDMA, and NVIDIA GPUDirect Storage (GDS)

• Deep understanding of the Linux I/O stack, including Block Device drivers, file system tuning (xfs, ext4), and client-side caching mechanisms

• Proficiency in one of Python, Ansible, or Terraform for automating storage cluster deployment and client configuration management

• Experience working within a System Integrator (SI), Storage Vendor (e.g., NetApp, Dell, Pure), or MSP environment

• Hands-on experience integrating storage with bare metal, and Kubernetes/Red Hat OpenShift

• Understanding of InfiniBand and RoCEv2 fabrics from a storage perspective (Congestion Control, Quality of Service)