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 Network Deployment team leads engineering and commissioning of high-performance networks across Nava's GPU clusters, including GPU fabrics, Ethernet leaf-spine, storage and out-of-band management networks. This is a hands-on leadership team where the fabric is treated as code.

Lead deployment and commissioning of high-performance GPU cluster networks, including InfiniBand, RoCE, Ethernet fabrics, and management networks. Own network automation, integration, performance validation, troubleshooting, and production readiness.

What You’ll Do

- Lead installation, configuration and production acceptance of InfiniBand, RoCE and high-speed Ethernet fabrics.
- Own topology implementation, switch configuration, cable/optics validation, routing and management connectivity.
- Validate RDMA fabric behavior, bandwidth, latency, congestion and distributed GPU communications.
- Build automated configuration, discovery, preflight and regression tests for repeatable multi-site network commissioning.




- Resolve cross-domain integration defects with compute/storage engineers and network OEMs.
- Manage network deployment engineers, technical milestones, standards, documentation and production handover.
- Tune PFC watermarks and ECN thresholds to keep RDMA lossless under all-reduce incast; validate rail-optimized topologies and adaptive routing on the GPU backend fabric.
- Define acceptance gates against measurable targets — NCCL all-reduce bus bandwidth within target % of line rate and near-zero PFC pause — using UFM (InfiniBand) and NetQ / Spectrum-X telemetry, plus GPUDirect RDMA and BlueField DPU offload validation.

What You’ll Need

- 10–15 years in data center network engineering including leading network deployment teams.
- Advanced BGP, EVPN/VXLAN, ECMP, leaf-spine architecture and Linux network troubleshooting.
- Solid understanding of InfiniBand and/or RoCEv2, RDMA, PFC/ECN and fabric congestion.
- Hands-on high-speed switches (100/200/400G+) and Python/Ansible or equivalent network automation.
- Experience with network validation and root-cause analysis at hardware and protocol layers.
- Within that, hands-on GPU / AI-datacenter exposure is what we weigh most — we value demonstrated depth over years, as the field is still emerging.
- NVIDIA networking, NCCL/fabric benchmarking and large AI/HPC cluster builds.

Skills: validation,cluster,rdma,automation,network deployment

📌 Head of AI Infrastructure — Cluster Deployment (Network) (Bengaluru)
🏢 NAVA
📍 Bengaluru