PrincipalSystemsEngineer

Principal Systems Engineer – GPU Supercluster Bringup About Us We are building AI infrastructure for frontier-scale workloads. Our platform is designed for high-density, high-performance GPU clusters that push the limits of power, networking, and distributed compute. As a startup, we move fast, operate with ownership, and expect technical leaders to define standards—not just follow them. The Role We are hiring a Principal Deployment Engineer to architect and lead the bringup of large-scale GPU clusters (hundreds to thousands of GPUs). This is a technical leadership role responsible for defining how we deploy, validate, and scale AI superclusters across sites. You will own the full lifecycle of deployment—from rack design and fabric architecture to cluster validation frameworks and production readiness standards. You will set the bar for performance, reliability, and operational excellence. This role combines deep hands-on expertise with system-level thinking and cross-functional leadership. What You’ll Do End-to-End Supercluster Bringup Ownership Define the technical standards for node, rack, and full-cluster bringup. Lead large-scale GPU cluster deployments (multi-rack, multi-pod environments). Architect high-performance network fabrics (IB, RoCE, Ethernet) optimized for AI workloads. Establish cluster-level acceptance criteria and validation frameworks. Performance & Fabric Architecture Tune and validate NCCL, RDMA, GPUDirect, and collective operations at scale. Identify and eliminate performance bottlenecks across hardware, topology, and firmware layers. Drive congestion control and fabric optimization strategies. Define performance benchmarking methodology for AI training workloads. Deployment Strategy & Scalability Design repeatable deployment models for multi-site expansion. Build automation frameworks for provisioning and cluster validation. Establish deployment SLAs, quality gates, and operational readiness standards. Reduce time-to-capacity while increasing