Role Summary The Senior Kubernetes Engineer, AI Infrastructure, owns the design and delivery of the backend infrastructure that powers the Firmus Kubernetes platform. This is a hands-on principal-level individual contributor role responsible for building production-grade cluster lifecycle, control-plane, networking, storage, security, observability, and automation for GPU-accelerated bare-metal environments. You will help set engineering standards, sign off on platform designs, and work across AI Platforms, Solutions Architecture & Delivery, networking, security, and operations to create a secure, multi-tenant platform that can be deployed consistently at AI-factory scale.

Key Responsibilities - Define and own the Kubernetes platform reference architecture across management and workload clusters, including control-plane topology, lifecycle, multi-tenancy, workload isolation, and failure-domain design. - Build and maintain backend services, APIs, controllers, operators, and automation to provision, configure, upgrade, scale, and retire Kubernetes clusters. - Implement repeatable bare-metal Kubernetes deployment and lifecycle workflows using infrastructure-as-code and provisioning technologies such as Cluster API, kubeadm, Redfish, PXE, Ironic, or Metal3. - Design and operate cluster networking (CNI, ingress, DNS, load balancing, network policy, service mesh); integrate high-performance NICs and interconnects as required for AI workloads. - Define persistent-storage patterns using CSI, Ceph, local NVMe, object storage, backup and disaster-recovery mechanisms suitable for sta

Role Summary The Senior Kubernetes Engineer, AI Infrastructure, owns the design and delivery of the backend infrastructure that powers the Firmus Kubernetes platform. This is a hands-on principal-level individual contributor role responsible for building production-grade cluster lifecycle, control-plane, networking, storage, security, observability, and automation for GPU-accelerated bare-metal environments. You will help set engineering standards, sign off on platform designs, and work across AI Platforms, Solutions Architecture & Delivery, networking, security, and operations to create a secure, multi-tenant platform that can be deployed consistently at AI-factory scale.

Key Responsibilities - Define and own the Kubernetes platform reference architecture across management and workload clusters, including control-plane topology, lifecycle, multi-tenancy, workload isolation, and failure-domain design. - Build and maintain backend services, APIs, controllers, operators, and automation to provision, configure, upgrade, scale, and retire Kubernetes clusters. - Implement repeatable bare-metal Kubernetes deployment and lifecycle workflows using infrastructure-as-code and provisioning technologies such as Cluster API, kubeadm, Redfish, PXE, Ironic, or Metal3. - Design and operate cluster networking (CNI, ingress, DNS, load balancing, network policy, service mesh); integrate high-performance NICs and interconnects as required for AI workloads. - Define persistent-storage patterns using CSI, Ceph, local NVMe, object storage, backup and disaster-recovery mechanisms suitable for sta