Live opening · Posted 3 days ago

Senior Infrastructure System Engineer

Nava · Bengaluru, Karnataka, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 3 days ago
CompanyNava
LocationBengaluru, Karnataka, India (On-site)
Work modeNo
SkillsPython, Kubernetes, Terraform
SourceLinkedin
ListedPosted 3 days ago

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About the role

Description supplied by the original job listing.

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

Work arrangement
No

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