About Nava

Nava is building next-generation AI infrastructure and inference platforms designed to power the future of AI. We are looking for a Head of GPU Cluster Engineering to lead the architecture, deployment, and operations of large-scale GPU clusters.

This is a highly strategic leadership role responsible for defining the engineering vision, driving execution across multiple infrastructure domains, and ensuring our GPU platforms deliver world-class performance, scalability, and reliability.

What You'll Do

Platform Leadership

- Own end-to-end engineering outcomes, from reference architecture through production operations.

- Define the technical vision, architecture, and operating model for large-scale GPU infrastructure.

- Establish engineering standards, design principles, and operational excellence across the platform.

- Drive platform scalability, resiliency, and performance to support rapidly growing AI workloads.

Architecture & Technical Strategy

- Lead the design and evolution of GPU cluster architectures across compute, networking, storage, orchestration, and observability.

- Evaluate and drive technology decisions around GPUs, interconnects, storage, Kubernetes, scheduling, and AI infrastructure software.

- Review and approve architecture decisions while balancing performance, reliability, cost, and operational complexity.

- Drive infrastructure standardization and automation across deployments.

Cross-Functional Leadership

- Lead execution across multiple engineering pillars:

- GPU Compute

- High-Speed Networking

- Storage

- Platform Engineering





- Site Reliability Engineering (SRE)

- Infrastructure Automation

- Partner closely with Product, Supply Chain, Data Centre Operations, and Customer Success teams to ensure successful platform delivery.

- Act as the technical escalation point for critical engineering decisions.

Delivery & Operational Excellence

- Own engineering readiness gates from design through production deployment.

- Drive release planning, operational reviews, risk assessments, and post-incident analysis.

- Establish SLAs, SLOs, and operational metrics for platform health and reliability.

- Champion automation, observability, incident management, and continuous improvement across the engineering organization.

Team Leadership

- Build, mentor, and scale a high-performing engineering organization.

- Develop technical leaders across infrastructure disciplines.

- Foster a culture of engineering excellence, ownership, collaboration, and innovation.

- Support hiring and talent development for critical infrastructure roles.

What We're Looking For

- 12 years of experience in infrastructure engineering, distributed systems, cloud platforms, or AI infrastructure.

- Proven experience leading large-scale infrastructure or platform engineering teams.





- Deep understanding of GPU clusters, AI infrastructure, HPC, or large-scale distributed systems.

- Solid expertise across:

- GPU Compute (NVIDIA ecosystem preferred)

- High-performance networking (InfiniBand, RoCE, RDMA)

- Kubernetes and container orchestration

- Distributed storage systems

- Infrastructure automation and observability

- Linux systems and platform engineering

- Experience designing highly available, scalable production infrastructure.

- Strong architectural thinking with the ability to balance technical excellence and business priorities.

- Excellent stakeholder management and cross-functional leadership skills.

Nice to Have

- Experience building AI factories, GPU cloud platforms, or large-scale inference infrastructure.

- Familiarity with CUDA, NCCL, Slurm, Ray, Kubeflow, or similar AI infrastructure technologies.

- Experience working with hyperscalers, cloud providers, or AI-first technology companies.

- Exposure to multi-region or global infrastructure deployments.

Why Join Nava?

- Build one of the world's leading AI infrastructure platforms.

- Lead the engineering strategy behind next-generation GPU clusters and AI factories.

- Work alongside world-class engineers solving some of the most challenging infrastructure problems in AI.

- Shape the future of AI infrastructure from architecture through production at global scale.

Skills: leadership,automation,platforms,gpu,reliability,storage,architecture,cloud,infrastructure,cluster,drive

📌 Head of GPU Cluster Engineering (Bengaluru)
🏢 NAVA
📍 Bengaluru