Senior AI Infrastructure Engineer — Network Operations

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 SRE & Operations team operates and continuously improves production GPU network reliability through deep technical troubleshooting, observability, safe automation and recurring-incident prevention.

Maintain reliability of production GPU cluster networks. Troubleshoot fabric failures, congestion, packet loss, and performance degradation. Build monitoring, automate remediation, manage incidents, and continuously improve network availability.

What You’ll Do

• Monitor fabric health, utilization, interface errors, congestion and link instability.

• Debug routing, RDMA failures, packet drops, GPU communication degradation and outages.

• Build telemetry dashboards, alert rules, health checks and automated network diagnostics.

• Contribute to incident response, fault isolation, root-cause analysis and remediation.

• Execute safe change windows, firmware upgrades and resilience testing.

• Work with compute/storage SREs and OEMs on cross-domain performance problems.

• Monitor PFC pause, ECN marks, buffer occupancy and link flaps; correlate with NCCL collective performance to catch congestion and silent RDMA packet loss early.

• Operate UFM (InfiniBand) and NetQ / Spectrum-X telemetry; hold lossless-RDMA as an SLI and drive recurring-incident elimination against NCCL bus-bandwidth and PFC-pause targets.

What You’ll Need

• 5–8 years in production network engineering or network SRE.

• BGP/EVPN, Linux networking, high-speed fabrics and advanced troubleshooting.

• Python/Go automation and operational monitoring experience.

• Proven responsibility for resolving live production incidents.

• 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.

• InfiniBand/RoCE, PFC/ECN, RDMA and NVIDIA fabric tooling.