AI infrastructure System Engineer Bangalore

Overview

AI Infrastructure Systems Engineer to design and operate GPU-fleet automation and monitoring systems for AI training and inference.

What you'll do

• Design and build fleet automation for provisioning, validating, deploying, upgrading, repairing, and retiring GPU clusters.
• Build AI infrastructure agents for automated deployment, failure root-cause analysis, incident triage, and autonomous remediation.
• Develop fleet intelligence to monitor hardware health, firmware, networking, storage, thermals, and workload performance.
• Build software to maximize 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 to manage infrastructure via software instead of manual operations.

What you'll need

• 3+ years of experience building distributed systems, infrastructure platforms, or large-scale backend software.
• Strong software engineering skills in Python, Go, or Rust.
• Experience building platforms, automation systems, or developer infrastructure.
• Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies.
• Strong systems thinking across hardware and software problem domains.
• An automation-first mindset to eliminate repeated manual work.

Nice to have

• Experience with GPU infrastructure and related technologies such as CUDA, NCCL, NVLink/NVSwitch, InfiniBand, or RoCE networking.
• Experience with bare-metal provisioning and lifecycle management.
• Experience with large-scale AI training or inference clusters.
• Experience with hardware health monitoring and predictive failure detection.
• Experience with distributed storage systems.
• Experience with AI agents and autonomous infrastructure operations.

Details

• Location: Bangalore, India.