Infrastructure System Engineer

Nava; Bengaluru; On-site; INR 2,800,000 - 4,200,000; Full time

Job summary

Nava in Bengaluru is building a next-generation Infrastructure Observability Platform to provide a unified view of modern datacenter and cloud infrastructure across physical, network, compute, GPU, storage, and software layers.

The platform will build a rich infrastructure graph linking assets, dependencies, workloads, tenants, and services, enabling real-time visibility into health, capacity, performance, topology, and utilization.

Qualifications

• 4-7 years building distributed systems, infrastructure platforms, or large-scale backend software.
• Strong software engineering skills in Go and Python.
• Experience with Linux, Kubernetes, Terraform, Ansible, or similar infra tech.
• Automation-first mindset; build systems to eliminate repetitive tasks.

Responsibilities

• Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention.
• Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation.
• Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers.
• Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators.
• Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads.
• Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations.
• Continuously improve deployment velocity, reliability, and operational efficiency through automation.
• Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure.

Skills

Distributed systems

Automation

Systems thinking

Go

Python

Tools

Go

Python

Kubernetes

Terraform

Ansible

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

We are building a next-generation Infrastructure Observability Platform that provides a unified view of modern datacenter and cloud infrastructure across physical, network, compute, GPU, storage, and software layers. The platform will build a rich infrastructure graph linking assets, dependencies, workloads, tenants, and services, enabling real-time visibility into health, capacity, performance, topology, and utilization. The role involves designing and building scalable data pipelines, asset and topology models, telemetry ingestion, correlation, and intelligent analytics for large-scale infrastructure environments. You will work across distributed systems, cloud infrastructure, Kubernetes, GPUs, networking, and data platforms to create a platform that turns infrastructure data into actionable operational intelligence.

What You’ll Do

• Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention.
• Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation.
• Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers.
• Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators.
• Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads.
• Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations.
• Continuously improve deployment velocity, reliability, and operational efficiency through automation.
• Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure.

What You’ll Need

• 4-7 years building distributed systems, infrastructure platforms, or large-scale backend software.
• Strong software engineering skills in Go, Python.
• Experience building platforms, automation systems, or developer infrastructure.
• Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies.
• Strong systems thinking with the ability to understand problems across hardware and software.
• A passion for solving complex infrastructure challenges through software.
• An automation-first mindset—if a task is repeated, your instinct is to build a system to eliminate it.

Skills: go (golang),cloud,kubernetes,ai infrastructure,gpu