Summary: Seeking a Senior DevOps Engineer to build, configure, and operate scalable Kubernetes and Linux compute foundations for GPU-heavy workloads, ensuring reliability and speed. Highlights: 1. Manage Kubernetes and Volcano scheduling for GPU-heavy workloads. 2. Automate workflows using Python and UNIX Shell scripting. 3. Partner with teams to improve scheduling efficiency and researcher workflows. We are delivering scalable Kubernetes and Linux compute foundations for GPU\-heavy workloads, and a Senior DevOps Engineer will help keep them reliable and fast. You will manage Kubernetes and Volcano scheduling, enforce quotas, and automate workflows using Python and UNIX Shell scripting in a client\-facing delivery setup. Apply now to join the team **Responsibilities** * Build, configure, and operate GPU\-enabled Kubernetes clusters and standalone Linux compute environments to maximize workload scheduling and performance * Run Volcano scheduling end\-to\-end, including queue creation, POD execution, GPU assignment, and enforcing namespace quotas * Manage Kubernetes environments comprehensively, including namespaces, RBAC, resource quotas, and workload isolation approaches * Create and support automation scripts in Python and Shell to streamline job submission, provisioning, and reporting * Partner with orchestration, optimization, and observability teams to improve scheduling efficiency, capacity utilization, and researcher workflows * Track infrastructure health and resource utilization, and provide data to support optimization and reporting needs * Recommend and drive enhancements to infrastructure, tooling, and automation workflows to improve performance, scalability, and usability * Maintain operational processes that enable a seamless and efficient researcher experience across AI and computational workloads **Requirements** * Minimum 3 years of experience in DevOps or infrastructure engineering roles within complex, large\-scale environments * Deep expertise in Kubernetes administration and orchestration, including namespaces, POD scheduling/distribution, PVC, NFS, and resource quota management * Practical experience using Volcano for GPU job execution, queue configuration, and workload prioritization integrated with Kubernetes * Demonstrated experience running GPU cluster environments in Kubernetes and on standalone Linux compute nodes * Advanced skills in Python scripting for infrastructure automation and strong UNIX Shell scripting such as Bash * Strong Linux administration knowledge, including troubleshooting, performance tuning, and configuration management * Good command of infrastructure automation and orchestration concepts and related tooling * Fluent English communication skills (spoken and written) to work directly with clients **Nice to have** * Working knowledge of Helm for Kubernetes application packaging * Experience with observability tooling such as Prometheus, Grafana and Loki * Exposure to Infrastructure as Code tooling, including Terraform * Familiarity with multi\-cloud Kubernetes options such as Amazon EKS and Google GKE * Knowledge of Azure Networking, including VPN, ExpressRoute and network security * Comfort with AI\-assisted coding tools like GitHub Copilot, ChatGPT and Claude * Understanding of hybrid (cloud and on\-premises) scheduling and resource optimization