Principal Engineer Cluster Deployment

About Nava

Nava is building next-generation AI infrastructure and inference platforms at global scale. We're looking for a Principal Engineer - Cluster Deployment to lead the successful deployment of large-scale GPU clusters across global data centres.

This is a high-impact execution role responsible for taking GPU clusters from hardware delivery to fully validated, production-ready infrastructure. You'll own deployment execution across sites, vendors, and cross-functional teams, ensuring every cluster is delivered on time, meets quality standards, and is ready for customer workloads.

What You'll Do

• End-to-End Cluster Deployment
• Own the deployment of GPU clusters from rack arrival through to tenant-ready production capacity.
• Plan, coordinate, and execute deployment activities across multiple global data centre locations.
• Drive installation, rack integration, power-up, hardware bring-up, firmware validation, and production readiness.
• Ensure deployments are completed safely, efficiently, and within agreed timelines.
• Deployment Execution
• Lead cluster bring-up activities, including hardware validation, network configuration, storage integration, and platform initialization.
• Oversee structured cabling, power validation, firmware upgrades, BIOS configuration, and infrastructure readiness.
• Coordinate deployment activities across internal engineering teams, hardware vendors, systems integrators, and data centre partners.
• Resolve deployment blockers and drive rapid issue resolution during implementation.
• Validation & Quality Assurance
• Develop and execute deployment validation procedures and acceptance criteria.
• Lead burn-in testing, stress testing, hardware diagnostics, and production readiness validation.
• Ensure clusters meet defined performance, stability, and reliability benchmarks before customer handover.
• Own first-pass acceptance and minimize deployment rework through robust quality processes.
• Vendor & Site Management
• Act as the primary technical lead during on-site deployments.
• Manage relationships with OEMs, contract manufacturers, data centre operators, and installation partners.
• Ensure deployment standards are consistently followed across all locations.
• Drive continuous improvement across deployment processes, documentation, and execution methodologies.
• Cross-Functional Collaboration
• Partner with GPU Cluster Engineering, Platform Engineering, Networking, SRE, Supply Chain, and Data Centre Operations teams.
• Ensure seamless transition from deployment to production operations.
• Support troubleshooting of deployment issues and coordinate engineering fixes where required.
• Operational Excellence
• Develop deployment playbooks, SOPs, checklists, and automation to improve deployment consistency.
• Track deployment metrics and identify opportunities to reduce deployment timelines and improve quality.
• Drive lessons learned reviews following every deployment.
  

Success Metrics

You Will Be Measured On

• Time-to-live for new GPU clusters
• First-pass deployment acceptance rate
• Deployment quality and reliability
• Reduction in deployment rework
• Deployment schedule adherence
• Production readiness at handover
• Deployment process standardization and automation
  
  

Qualifications

Required Qualifications

• 10+ years of experience in infrastructure deployment, data centre engineering, HPC, cloud infrastructure, or systems engineering.
• Proven experience deploying large-scale compute infrastructure, GPU clusters, HPC systems, or cloud platforms.
• Deep technical expertise in:
• Server and rack deployment
• GPU hardware platforms
• High-speed networking (InfiniBand, Ethernet, RDMA)
• Structured cabling and power systems
• Linux systems administration
• Firmware, BIOS, and hardware lifecycle management
• Infrastructure validation and production readiness
• Experience coordinating cross-functional deployment projects across multiple sites.
• Strong troubleshooting and problem-solving skills in complex infrastructure environments.
• Willingness to travel to domestic and international deployment locations.
  

Preferred Qualifications

• Experience with NVIDIA DGX, HGX, or similar GPU platforms.
• Familiarity with Kubernetes, cluster provisioning, automation, and Infrastructure-as-Code.
• Experience working with hyperscalers, AI infrastructure providers, or data centre operators.
• Exposure to HPC, AI factories, or large-scale inference platforms.
  
  

Skills: drive,platforms,infrastructure,data,gpu,production readiness,automation,cluster,validation,firmware,readiness