Summary: Seeking a Middle DevOps Engineer to operate Kubernetes and Linux GPU clusters, automate workflows, and partner with client-facing teams to build reliable, high-throughput compute platforms for advanced AI workloads. Highlights: 1. Operate Kubernetes and Linux GPU clusters for AI compute environments. 2. Automate workflows with Python and UNIX shell scripting. 3. Build reliable, high-throughput compute platforms for advanced AI workloads. We are delivering resilient Kubernetes and Linux platforms optimized for GPU scheduling and large\-scale automation in AI compute environments. As a Middle DevOps Engineer, you will operate Kubernetes (including Volcano) and Linux GPU clusters, automate workflows with Python and UNIX shell scripting, and partner with a client\-facing delivery team. Apply to help build reliable, high\-throughput compute platforms for advanced AI workloads. **Responsibilities** * Deploy, configure, and run GPU\-enabled Kubernetes clusters and standalone Linux compute environments while keeping scheduling and performance optimized * Implement and manage Volcano job scheduling, including queue setup, POD execution, GPU allocation, and namespace quota enforcement * Administer Kubernetes end to end, including namespaces, RBAC, resource quotas, and workload isolation approaches * Develop and maintain Python and Shell automation to simplify job submission, resource provisioning, and system reporting * Collaborate with orchestration, optimization, and observability teams to boost scheduling efficiency, improve capacity utilization, and streamline researcher workflows * Monitor infrastructure health and resource utilization, supplying data and feedback for optimization and reporting needs * Identify opportunities to improve infrastructure, tooling, and automation workflows to raise performance, scalability, and usability * Ensure operational processes deliver 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 in 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 the Volcano scheduler for GPU job execution, queue configuration, and workload prioritization integrated with Kubernetes * Proven ability to run GPU cluster environments in Kubernetes and 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