Senior AI Infrastructure Engineer — Compute & Storage Deployment

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 Compute & Storage Deployment team commissions NVIDIA GPU servers and high-performance storage systems, transforming bare-metal hardware into configured, diagnosed, benchmarked and accepted compute capacity.

Deploy NVIDIA GPU servers and distributed storage infrastructure. Perform hardware commissioning, firmware configuration, Linux provisioning, GPU diagnostics, storage integration, performance benchmarking, automation, troubleshooting, and production readiness validation.

What You’ll Do

• Bring up GPU servers, firmware, BMC, Linux images, CUDA drivers and operating system services.

• Validate GPU PCIe/NVLink connectivity, DCGM health and hardware burn-in results.

• Deploy parallel/distributed storage and test capacity, bandwidth, latency and recovery.

• Automate PXE/Redfish provisioning, baselines, diagnostics and configuration checks.

• Run GPU/cluster and storage acceptance benchmarks and close faults with OEMs.

• Document test results and hand over production-ready infrastructure.

What You’ll Need

• 5–8 years in Linux, server infrastructure, HPC or storage engineering.

• Hands-on bare-metal provisioning, firmware management and hardware troubleshooting.

• Linux/Python/Bash/Ansible capabilities and distributed storage fundamentals.

• Experience with server OEM tools, BMCs and hardware acceptance tests.

• Hands-on NVLink / NVSwitch bring-up and validation, and experience commissioning GB-class nodes (NVIDIA GB200 / GB300 NVL72 rack-scale systems).

• 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 GPU/DCGM/NCCL, WEKA, Lustre, BeeGFS, IBM Storage Scale or Ceph and Kubernetes/Slurm.