Senior DevOps Engineer

We are strengthening a client-facing delivery team that operates Kubernetes and Linux compute stacks for advanced AI workloads, including GPU scheduling with Volcano. You will automate day-to-day operations with Python and UNIX Shell, manage namespaces, RBAC, and quotas, and partner with researchers to keep platforms fast and dependable; apply now.

Deliver and support GPU-enabled Kubernetes clusters plus standalone Linux compute environments with strong scheduling behavior and throughput Run Volcano scheduling operations, including queue setup, POD execution, GPU allocation, and enforcement of namespace quotas Own Kubernetes administration across namespaces, RBAC, resource quotas, and workload isolation strategies Create and evolve Python and Shell scripts that automate job submission, resource provisioning, and system reporting Partner with orchestration, optimization, and observability teams to improve scheduling efficiency, utilization, and researcher workflows Track infrastructure health and resource utilization and provide input for optimization and reporting requirements Propose and drive improvements to infrastructure, tooling, and automation workflows to raise performance, scalability, and usability Support operational processes that ensure researchers have an efficient experience across AI and computational workloads At least 3 years of experience in DevOps or infrastructure engineering roles supporting complex, large-scale environments Expert proficiency in Kubernetes administration and orchestration, including management of namespaces, POD scheduling and distribution, persistent volume claims (PVC), network file systems (NFS), and resource quota management Hands-on experience with Volcano scheduler for GPU job execution, including queue configuration, workload prioritization, and integration with Kubernetes Proven experience managing GPU cluster environments, both within Kubernetes and on standalone Linux compute nodes, to support high-performance computing workloads Advanced Python scripting skills for automating infrastructure tasks, job submissions, and system reporting Proficiency in UNIX Shell scripting (e.g., Bash) for system automation and operational efficiency Strong Linux system administration skills, including troubleshooting, performance tuning, and configuration management for compute environments Solid understanding of infrastructure automation and orchestration concepts and tooling to enable scalable and reliable operations Fluent English communication skills (spoken and written) for direct client interaction and collaboration with cross-functional teams Experience with Helm package management for deploying and managing Kubernetes applications Familiarity with monitoring and observability solutions, particularly Prometheus, Grafana, and Loki, for infrastructure health and performance tracking Hands-on experience with Infrastructure as Code tools, such as Terraform, for automated provisioning and management of cloud resources Exposure to multi-cloud Kubernetes environments, including Amazon EKS and Google GKE, for broader orchestration experience Azure networking skills, including VPN configuration, ExpressRoute setup, and network security management, to support secure and scalable cloud deployments Familiarity with AI-assisted coding tools (e.g., GitHub Copilot, ChatGPT, Claude) to enhance development productivity and code quality Experience with hybrid (cloud and on-premises) scheduling and resource optimization to support flexible and efficient compute environments