Senior Cloud Platform Engineer, Kubernetes & Automation

nscaleoperationsukltd; United Kingdom; On-site; GBP 70,000 - 110,000; Full time

Job summary

Nscale is seeking a Platform Operations & Engineering leader to operate and improve Kubernetes-based platforms in production. You will own substantial parts of the platform, including cluster operations, deployment workflows, observability, and automation, enabling internal teams to run AI applications effectively.

You should bring hands-on experience with Kubernetes platforms, infrastructure automation, CI/CD, and GitOps-style workflows, plus strong Linux and networking fundamentals.

Qualifications

• Strong hands-on experience operating and improving Kubernetes-based platforms in production.
• Solid experience with infrastructure automation, CI/CD, configuration management, or GitOps-style workflows.
• Strong understanding of reliability engineering principles, including observability, incident response, failure analysis, and operational readiness.

Responsibilities

• Build and improve shared cloud-native platform capabilities used by internal engineering teams to run AI applications and services.
• Own significant parts of the platform area, including Kubernetes cluster operations, workload runtime configuration, deployment workflows, observability foundations, or environment automation.
• Improve the reliability, scalability, and supportability of platform services through practical engineering and operational enhancements.
• Develop automation, tooling, and configuration that reduce manual effort, improve consistency, and make the platform easier to use and operate.
• Apply software engineering where it creates leverage, including scripts, services, CI/CD automation, operational tooling, and platform integrations.

Skills

Kubernetes

Infrastructure automation

CI/CD

GitOps

Go

Python

Linux

Networking fundamentals

Tools

Git

CI/CD tooling

Job description

Nscale is seeking a Platform Operations & Engineering leader to operate and improve Kubernetes-based platforms in production. You will own substantial parts of the platform, including cluster operations, deployment workflows, observability, and automation, enabling internal teams to run AI applications effectively.

You should bring hands-on experience with Kubernetes platforms, infrastructure automation, CI/CD, and GitOps-style workflows, plus strong Linux and networking fundamentals.