Senior Cloud Platform Engineer

IT & Technology
London
July 17, 2026
Full Time

Job Overview

  • Date Posted
    July 17, 2026
  • Location
    London
  • Expiration date
    --

Job Description

The role:

The Cloud Platform team builds and operates the shared infrastructure and developer tooling that every engineering team at Liberis depends on. We’re now running all new services in GCP and are actively migrating onto GCP from our legacy Azure platform. As we scale our use of AI, we’re looking to add a Senior Cloud Platform Engineer with an emphasis on AI Enablement to help build and run the shared infrastructure our product teams depend on and to expand how we use AI across the platform. 

Our services are built in .NET, Node.js, and Python, primarily on both GCP and Azure. You’ll work across the platform stack, and you’ll be the person nudging us to make AI a practical, everyday part of how we build and operate. You’ll spot where AI can make the platform and the teams on it faster, from AI-assisted developer tooling to agents that take real work off people’s plates, and you’ll help turn those ideas into things people use, with the guardrails and cost controls that make them safe to run.

What you’ll get to do in the role:

  • Build and maintain the cloud infrastructure and tooling our product teams rely on, across compute, networking, CI/CD, and deployment on Kubernetes or Cloud Run.
  • Champion AI agent adoption across the platform: spot where agents can take on real work, prototype it, and turn the promising work into supported, reusable capabilities teams can build on.
  • Build the foundations for AI agents: integrations with Claude, the tools and services agents call, and the orchestration that ties them together.
  • Wire observability, guardrails, and cost controls into the AI agents and tooling we run, so they stay safe and predictable in production.
  • Work hands-on with the AI tooling and agent frameworks we build on — Claude in particular, which we use extensively — and bring what you learn back to the wider team.
  • Manage infrastructure with Terraform, keeping environments consistent, auditable, and reproducible.
  • Contribute to our Azure-to-GCP migration thinking, especially what it means for our AI tooling and agents.
  • Partner with product engineers to lower the barrier to using AI, writing the docs, templates, and examples that drive adoption.

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