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Mid-level metro role with niche Kubernetes control-plane skills yields medium competition density.
Deep Kubernetes control-plane and Go expertise create high domain specificity and low transferability across industries.
Explicit 5–9 years, mandatory 4+ years Kubernetes control-plane experience and strong Go make filters strict.
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Own and design Kubernetes control loops including CRDs, controllers, operators, reconcilers, and lifecycle management using Go and controller-runtime.
Build and operate multi-cluster control plane and workload-cluster agent encompassing onboarding, authentication, resource allocation, GPU/accelerator integration, secure remote access, and observability for a Kubernetes-native AI and MLOps platform.
Drive platform upgrade strategies, resource isolation, secure operations, and resilient design for unreliable distributed Kubernetes environments with strong operational correctness guarantees.
5+ years in software, platform, infrastructure, SRE, or cloud engineering with substantial hands-on Kubernetes experience.
Strong proficiency in Go programming language for building production services.
Deep understanding of Kubernetes internals including controllers, reconciliation, API machinery, RBAC, scheduling, networking, and workload lifecycle.
Experience building Kubernetes software (controllers, operators, Kubebuilder, controller-runtime, Operator SDK) not just operating clusters.
Experienced in designing and operating distributed Kubernetes-native control plane software with emphasis on control loops, idempotency, retries, partial failure tolerance, and eventual consistency.
Knowledgeable in multi-cluster management platforms, Kubernetes extension patterns, and secure remote cluster access.
Skilled in GPU and accelerator support for Kubernetes workloads, production troubleshooting across cluster components, and building observability into Kubernetes operators and agents.