Head of AI Infrastructure — Cluster Deployment

Nava; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Nava is seeking a seasoned program manager to lead end-to-end delivery of large-scale GPU infrastructure. You will drive timelines, coordinate site readiness, and manage multi-vendor relations to ensure on-time production handover.

Responsibilities include governance, risk management, and driving evidence-based decisions across OEMs, colocation providers, and internal platform teams. This is a senior, high-impact role in Bengaluru.

Qualifications

• 10–15 years of experience in top-tier consulting with tech transformations.
• Proven success leading large, cross-functional, multi-vendor programs with deadlines and budgets.
• Strong program decomposition, critical-path management, risk mitigation, and executive-level communication.
• Experience with GPU servers, data center commissioning, and AI/HPC deployments.

Responsibilities

• Build and own the integrated master delivery plan with milestones and acceptance gates for each new GPU cluster.
• Coordinate site operations, power and cooling readiness, logistics, OEM delivery, rack installation, network deployment, compute/storage bring-up.
• Lead weekly milestone governance, executive reviews, issue tracking, risk management, and recovery planning.
• Own delivery partner governance across colocation providers, OEMs, integrators, and suppliers.
• Collaborate on GPU diagnostics, burn-in, network/storage benchmarks, reliability testing, and customer acceptance evidence.
• Escalate blockers with options, business implications, owners, and deadlines backed by evidence.
• Run production-readiness and operational handover including inventory, runbooks, and support ownership.

Skills

Program management

Cross-functional leadership

Executive communication

Vendor management

Tools

GPU infrastructure

Data center operations

Job description

About Nava

Nava is a neocloud company purpose-built for the AI era. We design, deploy, and operate large-scale GPU infrastructure and deliver inference-as-a-service to teams building the next generation of AI products. Our platform runs on NVIDIA GPU systems, high-performance RDMA fabrics, and a fully automated, software-defined operations model. Every engineer at Nava works close to the metal, on infrastructure built to keep GPUs saturated and models serving.

About Nava

Nava is a neocloud company purpose-built for the AI era. We design, deploy, and operate large-scale GPU infrastructure and deliver inference-as-a-service to teams building the next generation of AI products. Our platform runs on NVIDIA GPU systems, high-performance RDMA fabrics, and a fully automated, software-defined operations model. Every engineer at Nava works close to the metal, on infrastructure built to keep GPUs saturated and models serving.

About The Role

Lead end-to-end delivery of large-scale GPU infrastructure—from infrastructure readiness through deployment, validation, and production handover. Own timelines, cross-functional coordination, vendor execution, risk management, acceptance milestones, and customer delivery commitments.

What You’ll Do

• Build and own the integrated master delivery plan—including critical path, milestones, dependencies, and acceptance gates for each new GPU cluster.
• Coordinate site operations, power and cooling readiness, logistics, OEM delivery, rack installation, network deployment, compute/storage bring-up, security, and platform teams.
• Lead weekly milestone governance, executive reviews, issue and decision tracking, delivery risk management, and recovery planning.
• Own delivery partner governance across colocation providers, OEMs, integrators, and key suppliers; resolve dependency and schedule conflicts.
• Collaborate with technical owners to plan GPU diagnostics, burn-in, network/storage benchmarks, reliability testing, and customer acceptance evidence.
• Escalate blockers early with clear options, business implications, assigned owners, and deadlines—ensuring committed dates are backed by evidence.
• Run formal production-readiness and operational handover—including inventory, as-built documentation, known issues, runbooks, and support ownership.

What You’ll Need

• 10–15 years of experience in top-tier consulting (e.g., MBB), with a focus on technology transformations, tech strategy, roadmap development, and technical program management.
• Demonstrated success leading large, cross-functional, multi-vendor programs with firm deadlines, budgets, interdependencies, and measurable outcomes.
• Strong program decomposition, critical-path management, risk mitigation, structured problem-solving, and executive-level communication skills.
• Ability to reason effectively about GPU servers, networking, storage, data center commissioning, and acceptance—even when specialist teams own the technical execution.
• Proven experience engaging with OEMs, data center providers, delivery leadership, and senior stakeholders.
• Experience deploying and validating cloud regions, hyperscale facilities, AI/HPC clusters, or other hardware-intensive production platforms.
• Hands-on exposure to GPU or AI-focused datacenter operations.

Skills: infrastructure,gpu cluster,oem delivery