DevOps Engineer – AI Infrastructure

Overview

Key Responsibilities

• Lead deployment and management of Linux-based AI infrastructure environments.
• Configure and maintain KVM virtualization platforms and GPU-enabled systems.
• Deploy and manage containerized LLM serving environments in production.
• Design scalable and secure Kubernetes-based infrastructure for AI workloads.
• Implement CI/CD pipelines, automation frameworks, and infrastructure-as-code practices.
• Apply security hardening, RBAC, encryption, secrets management, and audit-ready controls.
• Monitor GPU utilization, infrastructure health, and system performance.
• Support high availability, disaster recovery, backup, and failover strategies.
• Troubleshoot infrastructure, GPU runtime, networking, and platform stability issues.
• Prepare technical documentation, architecture diagrams, and operational runbooks.

Required Skills Experience

• 5+ years of experience in DevOps, Platform Engineering, or Infrastructure Engineering.
• Strong Linux administration experience including networking, storage, security hardening, and performance tuning.
• Hands-on experience working with NVIDIA GPU infrastructure including H100, A100, H200, or equivalent.
• Strong experience with CUDA drivers, GPU runtimes, GPU scheduling, and AI inference optimization.
• Experience deploying production-grade LLM serving platforms using technologies like vLLM, TensorRT-LLM, or Triton Inference Server.
• Strong hands-on experience with Docker, Kubernetes, and containerized AI workloads.
• Experience with Infrastructure as Code and automation tools such as Ansible.
• Strong understanding of DevSecOps practices, secure CI/CD pipelines, SAST integration, and secrets management.
• Experience working with PostgreSQL, vector databases such as Qdrant, and observability tools.
• Experience working in on-premise, air-gapped, or regulated enterprise environments.

Preferred

• Experience designing scalable AI infrastructure environments.
• Knowledge of HA/DR strategies and enterprise backup solutions.
• Strong troubleshooting and documentation skills.