Senior GPU development Engineer

We're looking for a Senior AI GPU Deployment Engineer to join our team What You Will Do Deploy integrate and validate multi-rack GPU-based compute platform deployments Deploy fabric configuration engines (Subnet Manager), observability platforms (UFM) and validate interconnect and fabric performance (nccl) Collaborate with network engineering team on topology implementation and optimization and storage engineering team on deployment and integration of high-performance storage environments supporting AI workloads (e.g. VAST Data) Configure settings and manage firmware updates for GPUs, NICs, BMC, BIOS and other components across large-scale clusters Contribute to infrastructure-as-code automation development for cluster provisioning and lifecycle management Contribute to improving and documenting repeatable deployment methodologies and scalable operational standards Query and analyze deployment outcomes using SQL for diagnostics and operational reporting 3+ years of infrastructure engineering or datacenter deployment experience 3+ years deploying large-scale AI, HPC, or GPU infrastructure Hands-on experience deploying and operating large GPU clusters in enterprise or hyperscale environments Strong expertise with: GPU architectures InfiniBand (NDR/XDR) and Ethernet GPU fabrics (Spectrum-X) NVLink, NVSwitch, and GPU-direct technologies Canonical MaaS and automated provisioning systems VAST Data or similar high-performance storage platforms Linux systems administration for HPC/AI workloads Infrastructure-as-Code and configuration management (Ansible) Python, Shell, and SQL for infrastructure automation and diagnostics Strong understanding of: RDMA, RoCE, and lossless Ethernet fabrics Cluster automation, observability, and lifecycle management