DevOps Engineer

Description

Summary: Seeking a DevOps Engineer to lead the deployment, configuration, and operation of AI workloads, KVM virtualization, and GPU-enabled environments for LLM inference. Highlights: 1. Lead deployment and configuration of on-prem Linux-based platforms for AI. 2. Architect and implement GPU-enabled environments for LLM inference. 3. Strong DevSecOps practices and HA/DR strategies. Position DevOps Engineer Duration 2 months Location Qatar (Onsite) Years of Experience 5\+ Years Notice Period Immediate Responsibilities * Lead deployment and configuration of on\-prem Linux\-based platformsfor AI workloads. * Design and configure KVM virtualization * Architect and implement GPU\-enabled environments for production LLM inference. * Deploy and operate containerized LLM serving stacksin production. * Design and validate GPU utilization, isolation, and health monitoring. * Integrate deployments with CI/CD pipelines and security controls. * Apply security hardening, RBAC, encryption, and audit\-ready configurations. * Design HA and DR strategies and prepare systems for future scale\-out. * Lead troubleshooting, performance tuning, and stabilization. * Produce architecture documentation, runbooks, and handover materials. * Primary Skills * 5\+ years of experience in DevOps, Platform Engineering, or Infrastructure Engineering roles. * Strong Linux system administration skills, including networking,storage, performance tuning, and security hardening.environments.equivalent).runtimes.Inference Server.vector databases (e.g., Qdrant), and observability tools. * Hands\-on experience deploying and operating LLMs in production on on\-premises * Proven experience managing GPU infrastructure using NVIDIA GPUs (H100, A100, H200 or * Hands\-on experience installing, configuring, and troubleshooting CUDA drivers and GPU * Experience with containerized workloads using Docker or OCI\-compliant runtimes. * Hands\-on experience with LLM serving frameworks such as vLLM, TensorRT\-LLM, or Triton * Experience designing and supporting GPU utilization, isolation, and performance monitoring. * Strong hands\-on experience with KVM virtualization in production. * Experience working with modern AI application stacks, including backend APIs, PostgreSQL, * Strong experience using Infrastructure as Code and automation tools, including Ansible. * Hands\-on experience designing and operating CI/CD pipelines in enterprise environments. * Hands\-on experience with Kubernetes on\-premisessetup. * Strong understanding and practical implementation experience of DevSecOps practices, * including secure pipelines, SAST integration, secrets management, and least\-privilege access. * Experience designing orsupporting high availability and disasterrecovery strategies, including backup, restore, and failover concepts. * Strong experience working in on\-prem, air\-gapped, orregulated environments Work Location: In person