DEVOPS ENGINEER (AI INFERENCE)
Gcore
Full-timemid
Job description
<p>As a DevOps Engineer, you will be responsible for designing, deploying, and maintaining infrastructure and services that enable scalable and secure AI inference workloads on-premises.</p><p><strong>What You Will Do</strong></p><ul><li>Design, develop, and maintain infrastructure for AI inference workloads, including GPU scheduling, model deployment pipelines, and data access patterns in on-prem environments</li><li>Build and manage monitoring and observability tools for AI inference platforms, including dashboards, alerts, and runbooks for model health and system performance</li><li>Collaborate with ML engineers and platform teams to design system architecture for AI workloads, integrate inference runtimes, and test performance at scale</li></ul>
<p><strong>What We're Looking For</strong></p><ul><li>Strong understanding of Kubernetes architecture, including CNI, CSI, operators, ingress/gateway, and control plane components.</li><li>Hands-on experience operating and troubleshooting production Kubernetes clusters.</li><li>Strong Linux and networking troubleshooting skills, including DNS, routing, firewalling, TLS, MTU, connectivity and performance issues.</li><li>Ability to develop automation and operational tooling using Python, Go, or Bash.</li><li>Experience with Terraform, Ansible, or similar IaC/configuration management tools.</li><li>Experience with VictoriaMetrics/Grafana or similar monitoring, alerting, and troubleshooting tools.</li><li>Strong experience with Git-based workflows and CI/CD pipelines.</li></ul><p><strong>Preferred Qualifications</strong></p><ul><li>Familiarity with Cluster API or similar Kubernetes cluster lifecycle management technologies.</li><li>Hands-on operation or administration of Slurm clusters.</li><li>Knowledge of Argo CD, GitOps workflows, Helm, or Helmfile.</li><li>Background working with managed platforms, PaaS, or cloud services.</li><li>Exposure to bare metal, GPU, HPC, or other high-performance computing environments.</li></ul><p><strong>Nice to Have</strong></p><ul><li>Familiarity with the NVIDIA GPU stack, RDMA/InfiniBand, or high-performance networking.</li><li>Knowledge of OpenStack or similar cloud infrastructure platforms.</li><li>Hands-on experience developing Kubernetes operators or controllers.</li></ul>
<p><strong>Benefits </strong></p><p>At Gcore, we want you to do your best work and enjoy the journey. Our benefits are designed to support your growth, well-being, and life beyond work: </p><ul><li>Competitive compensation</li><li>Flexible working hours and hybrid or remote options, depending on your role </li><li>Work from anywhere in the world for up to <strong>45 days per year</strong> </li><li>Private medical insurance for you and your family* </li><li>Extra paid vacation and sick leave days* </li><li>Support for life’s important moments and celebrations </li><li>Language courses to help you connect and grow </li><li>Modern, welcoming offices with snacks, drinks, and entertainment* </li><li>Team sports and social activities* </li></ul><p>*Benefits may vary depending on your location. </p><p><strong>Equal Opportunity Employer </strong></p><p>We provide equal opportunity to all applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity, gender expression, national origin, disability, or any other legally protected characteristics. </p>