Senior Manager, Cluster Engineering & Deployment

TensorWave’s mission is to deliver seamless, secure, reliable, and resilient AI compute at scale. Their cloud platform eliminates infrastructure barriers, allowing builders to focus on innovation rather than technical challenges.

About the Role

The Senior Manager, Cluster Engineering & Deployment oversees the entire process of transforming delivered racks into fully operational clusters. Key responsibilities include:

• Network bring-up, fabric cabling verification against port maps, GPU node integration with the fabric, cluster-level validation, and burn-in (including RCCL/collective performance testing).

• Acts as the critical gatekeeper for cluster acceptance into production, directly impacting cluster revenue timelines.

What You’ll Do

• Own and evolve the cluster deployment playbook, including staged bring-up, automated configuration push, link/optics validation, cabling verification, and fault triage during deployment windows.

• Lead deployment engineering across concurrent cluster builds, coordinating with team leads, on-site engineers, Data Center Integration teams, and cabling vendors.

• Drive deployment velocity by optimizing bring-up time per cluster through tooling, pre-staging, and defect-source elimination, setting measurable targets for the team.

• Establish and enforce defect feedback loops with Network Engineering, Layer One (cabling quality), and vendors (hardware/optics RMA patterns), ensuring accountability for resolution.

• Define and standardize spares, test equipment, and deployment tooling requirements across all sites.

Who You Are

Required Qualifications

• At least 10+ years of experience in network deployment, cluster/HPC bring-up, or large-scale infrastructure delivery, including managing engineers in a field/deployment setting.

• Hands-on experience with fabric bring-up at scale (hundreds of switches / thousands of links per deployment).

• Strong operational rigor, including building and enforcing playbooks, gates, metrics, and blameless defect loops.

• Proven team leadership with schedule accountability across multiple concurrent builds or sites.

Preferred Qualifications

• GPU cluster validation experience, including NCCL/RCCL benchmarking.

• Automation skills using Python and Ansible for deployment tasks.

• Depth in optics/link-layer debugging.

• Experience with acceptance testing as a commercial gate (revenue-linked).

• End-to-end ownership of cluster validation, including bandwidth/latency baselines, collective (RCCL) performance tests, burn-in criteria, and go/no-go acceptance gates.