Sr Kubernetes Engineer ( SME )
Neysa.ai · Mumbai · onsite · Posted 61d ago
Undisclosed5–10 yrsfulltimeSourced from
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About this role
Job Description
About the Role:
We are building and running mission-critical production infrastructure on Kubernetes. As a Senior Kubernetes Engineer, you will own the full stack from the underlying OS and container runtime through networking, storage, and the cluster control plane itself. You will engage across the full lifecycle: architecture, deployment, hardening, and day-2 operations for multi-cluster, multi-tenant environments. This is hands-on infrastructure work with direct ownership of production reliability.
What you will be doing:
Design, deploy, and operate production-grade Kubernetes clusters across bare-metal, cloud, and hybrid environments.
Manage cluster lifecycle end-to-end: provisioning, version upgrades, patching, scaling, and capacity planning
Architect and run multi-cluster/multi-tenant setups using Kamaji, Rancher (hosted control planes), and vCluster (virtual clusters)
Configure and troubleshoot CNI plugins (Calico, Cilium) pod networking, network policies, BGP, and eBPF dataplanes.
Own cluster DNS (CoreDNS) configuration, service discovery, and resolution troubleshooting.
Manage container runtime (containerd, CRI-O) and underlying OS: Linux tuning, kernel/sysctl parameters, systemd, cgroups
Deploy and operate service mesh (Istio, Cilium mesh) for traffic management
Manage persistent storage: PV/PVC, StorageClasses, CSI drivers (Rook/Ceph, Longhorn, cloud-native CSI)
Own the network stack: ingress controllers, load balancing, MetalLB/BGP, firewalling, and network troubleshooting
Implement GitOps and Infrastructure-as-Code (ArgoCD/FluxCD, Terraform, Helm) for cluster and workload delivery
Harden clusters: RBAC, Pod Security Standards, network policies, secrets management (Vault, Sealed Secrets), image scanning
Own backup and disaster recovery (Velero, etcd snapshotting) and run DR drills
Provide on-call production support: monitor cluster health, troubleshoot incidents, and drive root-cause resolution
Create comprehensive documentation, runbooks, and knowledge bases for operational continuity and knowledge transfer
What we need to see:
Core Kubernetes Infrastructure (5+ years)
Deep expertise in Kubernetes architecture: control plane, etcd, kube-apiserver, scheduler, controller-manager, kubelet
Proven experience designing, deploying, and troubleshooting production clusters at scale
Hands-on with multi-cluster/multi-tenant tooling Rancher, Kamaji, and/or vCluster (strongly preferred)
CNI expertise: Calico, Cilium network policy design, BGP, VXLAN/IPIP encapsulation, eBPF
Container runtime internals: containerd, CRI-O, runc configuration and troubleshooting
Strong Linux systems administration: kernel tuning, systemd, cgroups/namespaces, sysctl, package/OS lifecycle management
Storage: PV/PVC, StorageClasses, CSI drivers, Ceph/Rook, Longhorn, NFS
Service mesh experience: Istio, Linkerd, or Cilium service mesh
CoreDNS configuration, custom resolvers, and DNS troubleshooting in cluster environments
Networking depth: ingress controllers (NGINX, Envoy, Traefik), load balancing, MetalLB, and diagnostic tooling (tcpdump, iptables/nftables, conntrack)
Automation Infrastructure-as-Code:
Helm chart authoring and lifecycle management
GitOps workflows: ArgoCD or FluxCD
IaC and configuration management: Terraform, Ansible
CI/CD pipeline integration for cluster and application delivery
Scripting proficiency: Bash and Python (Go a plus)
Ways to stand out from the rest:
Kubernetes certifications: CKA, CKAD, CKS
Production experience with Rancher, Kamaji, and vCluster together (fleet/hosted-control-plane management)
Multi-cloud Kubernetes: EKS, AKS, GKE, and bare-metal
Experience with GPU-enabled clusters and AI/ML workload scheduling
Familiarity with AI/LLM serving stacks on Kubernetes vLLM, KServe, Triton Inference Server, GPU operator/device plugin, MIG partitioning
General AI infrastructure knowledge: model serving patterns, inference autoscaling, GPU scheduling constraints
Contributions to CNCF projects or an active open-source/GitHub presence
Minimum Qualifications:
Bachelor s degree in computer science, Electrical/Computer Engineering, or related field (or equivalent industry experience)
5+ years of hands-on production Kubernetes experience
Demonstrated ownership of CNI, DNS, storage, and networking within Kubernetes environments
Solid grounding in containerd/OS-level troubleshooting
Production on-call and incident-response experience.
Soft Skills:
Strong problem-solving and debugging abilities under production pressure
Ownership mindset with accountability for platform reliability and stability
Cross-functional collaboration with application, security, operations and platform teams
Proactive approach to continuous learning and staying current with the Kubernetes/CNCF ecosystem
Strong documentation and communication skills, with ability to defend design decisions in peer reviews
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Skills
AutomationBashAI infrastructurecomputer engineeringconfiguration managementAksAuthoringArgoCDContainerdebuggingdeploymentCephcloudContainer RuntimeCommunication SkillsArchitectureAdministrationAnsibleArtificial Intelligence
About Neysa.ai
Neysa.ai
IT Services & Consulting
100
employees
2023
3 years old
Mumbai, Maharashtra
US
₹58.2L PA avg
Avg at Neysa.ai
About
At Neysa we accelerate AI adoption through purpose-built systems and services, enabling organisations to seamlessly integrate AI into their operations and drive real-world impact.
Industries
IT Services & Consulting
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