Employer description & source details
To be successful in this role you have: Experience leveraging or critically thinking about how to integrate AI into engineering and platform work—AI-powered tooling, automated operational workflows, agentic systems for fleet visibility and operations, or reasoning about AI’s impact on how infrastructure is built and run. 8+ years of experience designing, building, and operating large-scale distributed systems and cloud-native platforms in production environments. Demonstrated experience building and operating Kubernetes platform infrastructure at scale, with ownership of platform capabilities through deployment, upgrades, and production operations. Hands-on developing Kubernetes Operators, Admission Controllers, or other platform extensions using Kubebuilder, Operator Framework, or similar technologies. Experience operating both managed Kubernetes services (EKS, AKS, GKE) and self-managed Kubernetes environments. Experience supporting cloud-native database platforms, large-scale data infrastructure, or stateful services on Kubernetes. Strong software engineering expertise in Go, with hands-on experience developing Kubernetes Operators, Controllers, Custom Resource Definitions (CRDs), and platform automation capabilities. Deep understanding of Kubernetes architecture, including orchestration, scheduling, security, storage, networking, and workload management. Proven experience operating stateful and distributed workloads on Kubernetes, including databases, data services, or other mission-critical platform components. Experience with public cloud platforms (AWS, Azure, or GCP), including compute, networking, security, and identity management services. Strong background designing and building microservices, event-driven systems, and distributed application architectures. E
Extracted skills: go, redis, aws, azure, gcp, kubernetes, terraform, machine learning, security, operations