DevOps Engineer – AI Infrastructure

We are hiring an experienced DevOps Engineer with strong expertise in AI infrastructure, GPU environments, Kubernetes, and enterprise-grade platform engineering. This role is ideal for professionals who have worked on deploying and managing production-level LLM environments within secure on-premise infrastructures.

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.