Head of AI Infrastructure — Cluster Operations & Service Delivery

Nava; Bengaluru; On-site; INR 4,500,000 - 6,000,000; Full time

Job summary

Nava is seeking a senior Cluster Operations & Service Delivery lead in Bengaluru to own end-to-end operational delivery for its production GPU clusters. You will drive governance, incident management, and cross-functional collaboration across network, compute, storage, and security teams.

You will manage executive dashboards, KPI scorecards, and escalation paths while coordinating with enterprise customers and partners to ensure SLA compliance and continuous service improvements.

Qualifications

• 10–15 years of experience in top-tier consulting (MBB), focusing on technology transformations, tech strategy roadmap and technical program management.
• Track record leading multi-stakeholder transformations or large technical operations programs with measurable commercial and customer outcomes.
• Strong command of executive communication, data-driven governance, structured problem solving, conflict resolution and high-stakes escalation management.
• Enough fluency in data centers, cloud services, compute, networking and storage to challenge assumptions and make sound trade-offs with engineering leads.
• Experience developing SLA/KPI frameworks, incident governance, vendor operating models and performance reviews.
• Experience with customer-facing cloud infrastructure, AI/HPC deployments or global 24x7 operations.
• Hands-on GPU / AI-datacenter exposure.

Responsibilities

• Own end-to-end operational delivery against customer SLAs, availability objectives and support commitments across multiple GPU regions.
• Establish operating governance: service reviews, KPI scorecards, executive dashboards, action logs, escalation paths and decision forums.
• Serve as overall incident-delivery lead for critical issues: orchestrate technical owners, customer updates, vendor escalation, recovery actions and post-incident follow-through.
• Drive cross-functional problem resolution across network, GPU compute, storage, security, data centers and platform teams without replacing their technical owners.
• Maintain integrated operational risk, dependency and improvement plans; connect recurring incidents to corrective work and measured outcomes.
• Lead relationships with enterprise customers, OEMs, colocation providers and internal executives on reliability and service performance.
• Standardize service handover, change governance, capacity reviews and quarterly operational business reviews as the fleet scales.

Skills

Operational governance

SLA frameworks

Executive communication

Data-driven governance

Program management

Vendor management

Stakeholder leadership

Cloud infrastructure

GPU/AI datacenter

Tools

AI/ML deployments

24x7 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

The Cluster Operations & Service Delivery function owns customer-facing operational reliability across Nava’s production GPU clusters. You set the cadence, accountability and executive transparency that keep service commitments consistently met across network, compute, storage, security and external partners.

Own end-to-end operational service delivery across GPU clusters, ensuring SLA compliance, incident resolution, customer satisfaction, operational governance, vendor coordination, performance reporting, and seamless execution across network, compute, storage, and security teams.

What You’ll Do

• Own end-to-end operational delivery against customer SLAs, availability objectives and support commitments across multiple GPU regions.
• Establish operating governance: service reviews, KPI scorecards, executive dashboards, action logs, escalation paths and decision forums.
• Serve as overall incident-delivery lead for critical issues: orchestrate technical owners, customer updates, vendor escalation, recovery actions and post-incident follow-through.
• Drive cross-functional problem resolution across network, GPU compute, storage, security, data centers and platform teams without replacing their technical owners.
• Maintain integrated operational risk, dependency and improvement plans; connect recurring incidents to corrective work and measured outcomes.
• Lead relationships with enterprise customers, OEMs, colocation providers and internal executives on reliability and service performance.
• Standardize service handover, change governance, capacity reviews and quarterly operational business reviews as the fleet scales.

What You’ll Need

• 10–15 years of experience in top-tier consulting (MBB), focusing on technology transformations, tech strategy roadmap and technical program management.
• Track record leading multi-stakeholder transformations or large technical operations programs with measurable commercial and customer outcomes.
• Strong command of executive communication, data-driven governance, structured problem solving, conflict resolution and high-stakes escalation management.
• Enough fluency in data centers, cloud services, compute, networking and storage to challenge assumptions and make sound trade-offs with engineering leads.
• Experience developing SLA/KPI frameworks, incident governance, vendor operating models and performance reviews.
• Experience with customer-facing cloud infrastructure, AI/HPC deployments or global 24x7 operations.
• Hands-on GPU / AI-datacenter exposure.

Skills: infrastructure,gpu,datacenter