Summary: Join a client-facing team to support and enhance Kubernetes environments with Volcano, operate Linux compute nodes, and deliver automation for AI workloads. Highlights: 1. Support and enhance Kubernetes for GPU workloads 2. Develop automation in Python and Bash for AI jobs 3. Partner to improve scheduling efficiency and researcher workflows We are building scalable Kubernetes and Linux infrastructure designed for GPU workloads, efficient scheduling, and repeatable automation at scale. As a Middle DevOps Engineer, you will support and enhance Kubernetes environments with Volcano, operate Linux compute nodes, and deliver automation in Python and Bash within a client\-facing team. Apply to help researchers run AI jobs smoothly on reliable compute platforms. **Responsibilities** * Install, configure, and operate GPU\-enabled Kubernetes clusters and standalone Linux compute environments to maintain optimized scheduling and performance * Configure and administer Volcano job scheduling, including queue setup, POD execution, GPU allocation, and namespace quota enforcement * Manage Kubernetes end to end, covering namespaces, RBAC, resource quotas, and workload isolation approaches * Build and maintain Python and Shell automation to streamline job submission, resource provisioning, and system reporting * Partner with orchestration, optimization, and observability teams to improve scheduling efficiency, increase capacity utilization, and simplify researcher workflows * Track infrastructure health and resource utilization, providing data and feedback for optimization and reporting needs * Drive enhancements to infrastructure, tooling, and automation workflows to improve performance, scalability, and usability * Support operational processes that ensure a smooth and efficient experience for researchers running diverse AI and computational workloads **Requirements** * Hands\-on background with 2\+ years of experience in DevOps or infrastructure engineering within complex, large\-scale environments * Strong expertise in Kubernetes administration and orchestration, including namespaces, POD scheduling/distribution, PVC, NFS, and resource quota management * Practical experience with the Volcano scheduler for GPU job execution, queue configuration, and workload prioritization integrated with Kubernetes * Proven ability to operate GPU cluster environments in Kubernetes as well as on standalone Linux compute nodes * Advanced Python scripting skills for infrastructure automation, plus proficiency in UNIX Shell scripting such as Bash * Strong Linux system administration skills, including troubleshooting, performance tuning, and configuration management * Solid understanding of infrastructure automation and orchestration concepts and related tooling * Fluent English communication skills (spoken and written) for direct client interaction **Nice to have** * Knowledge of Helm package management for Kubernetes applications * Familiarity with monitoring and observability solutions, particularly Prometheus, Grafana, and Loki * Skills in Infrastructure as Code tools such as Terraform * Background in multi\-cloud Kubernetes environments including Amazon EKS and Google GKE * Understanding of Azure Networking including VPN, ExpressRoute, and network security * Familiarity with AI\-assisted coding tools such as GitHub Copilot, ChatGPT, and Claude * Experience with hybrid (cloud and on\-premises) scheduling and resource optimization