About TensorWave

Our mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform that eliminates infrastructure barriers, empowering builders to focus on innovation instead of fighting their stack. Because breakthrough AI should move at the speed of ideas, not infrastructure.

About the Role

The Senior Manager, Cluster Engineering & Deployment owns and runs the machine that turns delivered racks into accepted clusters: 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), and the acceptance gate into production. This is one of the most schedule-critical roles in the pillar cluster revenue starts when this team says a cluster is ready.

What You’ll Do

• Own the cluster deployment playbook and drive its evolution: staged bring-up, automated config push, link/optics validation, cabling verification against L1 port maps, and fault triage during deployment windows.

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

• Drive deployment velocity engineering: cut bring-up time per cluster through tooling, pre-staging, and defect-source elimination, and set the targets the team is measured against.

• Own defect feedback loops to Network Engineering (design), Layer One (cabling quality), and vendors (hardware/optics RMA patterns), holding those partners accountable to resolution.

• Define spares, test equipment, and deployment tooling requirements per site, and standardize them across sites.

Who You Are

Required Qualifications

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

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

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

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

Preferred Qualifications

• GPU cluster validation experience (NCCL/RCCL benchmarking).

• Automation skills (Python, Ansible) applied to deployment.

• Optics/link-layer debugging depth.

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

• Own cluster validation end to end: bandwidth/latency baselines, collective (RCCL) performance tests, burn-in criteria, and go/no-go acceptance gates and raise the bar on each as the fleet scales.

What We Offer

• Stock Options

• 100% paid Medical, Dental, and Vision insurance for Employees

• Company Health Savings Account Contributions

• 100% paid Short Term and Long Term Disability Insurance for Employees

• Life and Voluntary Supplemental Insurance Options

• Other Insurance Options, such as Pet & Legal Insurance

• Various Supplementary Health Benefits, such as discounted Virtual Healthcare Appointments and Serious Illness Support

• Flexible Spending Account

• 401(k)

• Employee Assistance Program

• Flexible PTO

• Paid Holidays

• Parental Leave

• Other In-Office Perks

Equal Employment Opportunity

TensorWave is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of any protected status under applicable law.

Reasonable Accommodations

TensorWave provides reasonable accommodations in accordance with applicable laws. If you require accommodation during the hiring process, please contact [email protected].

Employment Eligibility

All offers of employment are contingent upon verification of identity and authorization to work in the United States, as required by law.

Background Checks

Where permitted by law, employment may be contingent upon the successful completion of a job-related background check.

Data Privacy Notice

By submitting an application, you acknowledge that TensorWave may collect, use, and retain your personal information for recruiting and employment-related purposes in accordance with applicable data privacy laws.