Summary: Seeking a Middle DevOps Engineer to operate and automate resilient Kubernetes and Linux GPU platforms for advanced AI workloads, collaborating with a client-facing delivery team. Highlights: 1. Build reliable, high-throughput compute platforms for advanced AI workloads. 2. Automate workflows with Python and UNIX shell scripting. 3. Administer Kubernetes end to end for optimized GPU scheduling. 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