Hiring: Senior AI Infrastructure Engineer, Kubernetes Company: Firmus Technologies Location: San Francisco, CA Job Posted Time: 2026-09-17 07:05:22 Employment Type: Full-time / Hybrid Target Skills & Keywords : Ansible, ArgoCD, BGP, Bash, CI/CD, DNS, Elasticsearch, GitHub Actions, GitLab CI, GitOps, Grafana, Jenkins, Kubernetes, Linux, Load Balancing, Node.js, OpenTelemetry, Prometheus, Python, RBAC, Rust, Service Mesh, Terraform, Webhooks About the job Experience: •7+ years of progressive infrastructure, systems, or platform engineering experience, including substantial ownership of production Kubernetes platforms and at least 3 years operating at senior staff, principal, or equivalent level. •Deep knowledge of Kubernetes internals, including the API server, etcd, scheduler, controller manager, kubelet, admission, CRI, CNI, CSI, reconciliation patterns, cluster performance, upgrades, and control-plane failure modes. •Demonstrated experience designing, building, and operating highly available, large scale and multi-cluster Kubernetes platforms on bare metal, private cloud, or hybrid infrastructure. •Strong software engineering ability in Go and/or Rust, with practical Python and Bash skills; experience building Kubernetes operators, controllers, admission webhooks, CLIs, or platform services. •Expert Linux systems knowledge, including namespaces, cgroups, systemd, kernel, host networking and container runtime behaviour, performance analysis, and low-level troubleshooting. Required Skills: •Define and own the Kubernetes platform reference architecture across management and workload clusters, including control-plane topology, cluster lifecycle, multi-tenancy, workload isolation, and failure-domain design. •Build and maintain the backend services, APIs, controllers, operators, and automation required to provision, configure, upgrade, scale, and retire Kubernetes clusters reliably. •Engineer repeatable bare-metal Kubernetes deployment and lifecycle workflows using infrastructure-as-code and automated provisioning technologies such as Cluster API, kubeadm, Redfish, PXE, Ironic, or Metal3. •Design and operate cluster networking across CNI, ingress, service discovery, DNS, load balancing, network policy, and service mesh; integrate Multus, SR-IOV, BGP, InfiniBand, or RoCE where required for high-performance AI workloads. •Define persistent-storage and data-service patterns using CSI, Ceph, local NVMe, object storage, backup and restore, and disaster-recovery mechanisms appropriate for stateful platform and AI workloads. •Integrate and productionise NVIDIA GPU and Network Operators, device plugins, drivers, DCGM telemetry, scheduling, quotas, and topology-aware placement for multi-node accelerated workloads. •Establish GitOps and CI/CD patterns for platform software, configuration, policy, and release management, with safe testing, progressive rollout, rollback, and upgrade practices. •Build platform security into the architecture through identity and access control, RBAC, secrets management, policy-as-code, image and software-supply-chain controls, tenant isolation, and auditable change management. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!