Senior Kubernetes Engineer

Zohorecruit; United Arab Emirates; Remote; AED 280,000 - 520,000; Full time

Job summary

Techsa is seeking a Senior Kubernetes Engineer to own critical areas of our technology and data platform. You will design reference deployments and run production clusters on client-owned infrastructure including bare metal, private cloud, and sovereign environments.

Collaborate across engineering, product, data, design, and business teams to translate requirements into scalable solutions, enforce security and RBAC, and ensure high availability and zero-downtime upgrades.

Qualifications

• 7+ years of relevant professional experience.
• Extensive hands-on Kubernetes on bare metal and private networks.
• Deep knowledge of CNI, CSI and persistent storage, ingress and load balancing.
• Experience with etcd operations, Helm and GitOps tools (ArgoCD or Flux).
• Experience building and operating production clusters on bare metal or private cloud.
• Air-gapped deployment capabilities and image mirroring.
• Running stateful workloads (Kafka, Flink, Spark, databases) on Kubernetes.
• RBAC design and network security in regulated environments.

Responsibilities

• Own and deliver solutions from requirements through implementation.
• Collaborate with engineering, product, data, design, and business stakeholders to translate requirements into scalable solutions.
• Apply engineering and domain expertise to build reliable capabilities.
• Contribute to architecture, standards, and technical decisions.
• Identify and address performance, scalability, or reliability risks.
• Ensure solutions integrate with existing systems and platform components.

Skills

Kubernetes

Bare metal

CNI

CSI & Storage

Ingress & LB

etcd operations

Helm

ArgoCD or Flux

Terraform

Air-gapped deployment

Stateful workloads

RBAC design

Tools

Kubernetes

Helm

ArgoCD or Flux

Terraform

CNI

CSI & Storage

Ingress & LB

Air-gapped deployment

Job description

We are looking for a Senior Kubernetes Engineer to join our team and take ownership of key areas within our technology and data platform. Owns Kubernetes on client owned infrastructure: bare metal, private cloud, and sovereign environments. Designs the reference deployment that a client operations team can install and run.

Key Responsibilities

• Own and deliver solutions within the scope of the role, from requirements and technical/design decisions through implementation and continuous improvement.
• Work closely with engineering, product, data, design, and business stakeholders to translate requirements into practical, scalable solutions.
• Apply strong engineering and/or domain expertise to build reliable, maintainable, and production-ready capabilities.
• Contribute to architecture, standards, documentation, quality, and technical decision-making appropriate to the role.
• Identify performance, scalability, data quality, usability, reliability, or operational risks and address them proactively.
• Collaborate across teams to ensure solutions integrate effectively with existing systems and platform components.

Requirements

• Experience: 7+ years of relevant professional experience.
• Strong hands-on experience with: Kubernetes on bare metal, CNI, CSI and persistent storage, ingress and load balancing, etcd operations, Helm, ArgoCD or Flux, Terraform, air gapped deployment.
• Built and operated production clusters on bare metal or private cloud, not only EKS, AKS, or GKE.
• Deep on what managed services abstract away: CNI behaviour, persistent storage, ingress and load balancing without a cloud provider, PKI and certificates, etcd backup and recovery.
• Air gapped or restricted network deployment, including image mirroring and offline installation.
• Runs stateful data workloads on Kubernetes: Kafka, Flink, Spark, databases, and their operators.
• Hardening in regulated environments: policy enforcement, network policy, secrets management, RBAC design.
• Capacity planning, high availability, disaster recovery, and zero downtime upgrades.

Preferred Qualifications

• GPU scheduling and node management for AI workloads.
• On premises deployment in telco or banking environments.
• Experience in client data centres and security reviews.