Principal Deployment Engineer

Principal Deployment 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 reliability.

Technical Leadership

• Serve as the escalation point for complex bringup and performance issues.
• Mentor senior engineers and shape infrastructure best practices.
• Influence hardware selection, rack topology, and data center design decisions.
• Partner with executive leadership on infrastructure scaling strategy.

What We're Looking For

Required

• 10+ years of experience in large-scale infrastructure or HPC environments.
• Proven experience bringing up large GPU clusters (hundreds+ GPUs).
• Deep expertise in high-speed networking (InfiniBand, RoCE, Ethernet fabrics).
• Strong understanding of server architecture (PCIe, NUMA, memory hierarchy).
• Experience debugging performance issues across compute and network layers.
• Strong automation and systems-level thinking.

Strongly Preferred

• Experience scaling AI training clusters for frontier models.
• Experience with liquid cooling or ultra-high-density deployments.
• Knowledge of distributed storage systems (Lustre, Ceph, NVMe-oF).
• Experience defining infrastructure standards in a fast-growing organization.

What Success Looks Like

• Superclusters are brought online quickly, predictably, and at peak performance.
• Deployment processes scale from first cluster to multi-site expansion.
• Infrastructure becomes a competitive advantage.
• You define the technical blueprint for how we scale AI infrastructure.