Summary: Join a client-focused delivery team as a Senior DevOps Engineer managing automated, high-performance Kubernetes and Linux infrastructure for GPU-intensive AI and research compute. Highlights: 1. Manage Kubernetes and Volcano scheduling for GPU-intensive AI workloads 2. Build automation with Python and UNIX shell scripting for dependable operations 3. Focus on performance, scheduling quality, and researcher workflows We are delivering automated, high\-performance Kubernetes and Linux infrastructure that supports GPU\-intensive AI and research compute. In this Senior DevOps Engineer role, you will manage Kubernetes administration and Volcano scheduling, tune Linux environments, and build automation in Python and UNIX shell scripting for dependable operations. Apply now to join a client\-focused delivery team **Responsibilities** * Set up, configure, and maintain GPU\-enabled Kubernetes clusters and standalone Linux compute environments with a focus on performance and scheduling quality * Operate Volcano scheduling for GPU workloads, including queues, POD execution, GPU allocation, and namespace quota enforcement * Run Kubernetes administration activities across namespaces, RBAC, resource quotas, and workload isolation strategies * Build and support Python and Shell scripts to automate job submission, resource provisioning, and operational reporting * Partner with orchestration, optimization, and observability teams to improve scheduling efficiency, capacity utilization, and researcher workflows * Track infrastructure health and utilization, producing insights that feed optimization and reporting requirements * Drive improvements in infrastructure, tooling, and automation workflows to raise scalability, performance, and usability * Support operational practices that enable an efficient experience for researchers running varied AI and computational workloads **Requirements** * Minimum 3 years of professional experience in DevOps or infrastructure engineering on complex, large\-scale platforms * Expert proficiency with Kubernetes operations, including namespaces, POD scheduling/distribution, PVC, NFS, and resource quota management * Practical experience using Volcano for GPU job execution, queue configuration, workload prioritization, and Kubernetes integration * Proven ability to manage GPU clusters on Kubernetes as well as on standalone Linux compute nodes * Advanced skill in Python for automation and strong proficiency in UNIX Shell scripting (e.g., Bash) * Strong Linux administration skills, including troubleshooting, performance tuning, and configuration management * Solid grasp of infrastructure automation and orchestration principles and common tooling * Fluent English communication skills (spoken and written) for direct client interaction **Nice to have** * Helm experience for packaging and managing Kubernetes applications * Observability background with Prometheus, Grafana, and Loki * Terraform experience for Infrastructure as Code * Multi\-cloud Kubernetes experience across Amazon EKS and Google GKE * Azure Networking skills, including VPN, ExpressRoute, and network security * Exposure to AI\-assisted coding tools (e.g., GitHub Copilot, ChatGPT, Claude) * Hybrid (cloud \+ on\-premises) scheduling and resource optimization experience