Senior Kubernetes Engineer

This is a remote position.

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.