Summary: Join as a Senior DevOps Engineer to build and operate scalable, GPU-ready Kubernetes platforms for AI and research workloads, focusing on reliable orchestration and performance in a client-facing delivery setup. Highlights: 1. Operate Kubernetes and Linux compute environments for AI and research workloads 2. Automate workflows with Python and UNIX shell scripting 3. Collaborate on orchestration, optimization, and observability We are building scalable, GPU\-ready Kubernetes platforms for AI and research workloads, focusing on reliable orchestration and performance. As a Senior DevOps Engineer, you will operate Kubernetes and Linux compute environments, run Volcano scheduling, and automate workflows with Python and UNIX shell scripting in a client\-facing delivery setup. Apply now to help deliver efficient compute at scale **Responsibilities** * Deploy, configure, and sustain GPU\-enabled Kubernetes clusters and standalone Linux compute environments to maximize scheduling efficiency and performance * Implement and operate Volcano job scheduling, including queue setup, POD execution, GPU allocation, and namespace quota enforcement * Administer Kubernetes end\-to\-end, covering namespaces, RBAC, resource quotas, and workload isolation approaches * Create and maintain Python and Shell automation to simplify job submission, resource provisioning, and system reporting * Collaborate with orchestration, optimization, and observability teams to improve scheduling efficiency, capacity utilization, and researcher workflows * Monitor platform health and resource utilization, sharing data and feedback to support optimization and reporting needs * Recommend and drive enhancements to infrastructure, tooling, and automation workflows to improve performance, scalability, and usability * Ensure operations provide a smooth and efficient experience for researchers across diverse AI and computational workloads **Requirements** * Minimum 3 years of experience in DevOps or infrastructure engineering roles within complex, large\-scale environments * Expert\-level Kubernetes administration knowledge, including namespaces, POD scheduling/distribution, PVC, NFS, and resource quota management * Hands\-on experience with Volcano scheduler for GPU job execution, queue configuration, workload prioritization, and Kubernetes integration * Demonstrated experience running GPU cluster environments in Kubernetes and on standalone Linux compute nodes * Advanced Python scripting skills for infrastructure automation, plus proficiency in UNIX Shell scripting (e.g., Bash) * Strong Linux system administration capability, including troubleshooting, performance tuning, and configuration management * Solid understanding of infrastructure automation and orchestration concepts and supporting tooling * Fluent English communication skills (spoken and written) for direct client interaction **Nice to have** * Helm for Kubernetes application packaging and releases * Monitoring and observability tooling, especially Prometheus, Grafana, and Loki * Infrastructure as Code tools such as Terraform * Multi\-cloud Kubernetes exposure (Amazon EKS, Google GKE) * Azure Networking knowledge including VPN, ExpressRoute, and network security * Familiarity with AI\-assisted coding tools (e.g., GitHub Copilot, ChatGPT, Claude) * Experience with hybrid (cloud \+ on\-premises) scheduling and resource optimization