DevOps Contract

London (Hybrid)
SFIA 5: £450/day

About the Role

We are supporting the delivery of a major enterprise-scale AI platform designed to enable secure, scalable, and production-ready use of Generative AI and Machine Learning within a highly regulated, large-scale government environment.

This is not a traditional DevOps engineering role focused solely on building pipelines. Instead, we are looking for experienced DevOps and process improvement specialists who can work directly with engineering teams to identify process debt, improve software delivery practices, and prepare teams for effective AI-assisted development.

The successful candidates will embed within delivery teams, assess current DevOps maturity, remove delivery bottlenecks, and help create the conditions required for AI coding assistants and agentic workflows to deliver meaningful value.

Key Responsibilities

• Assess existing DevOps practices across delivery teams including:

  • CI/CD pipelines
  • Branching strategies
  • Release management
  • Testing approaches
  • Environment management
  • Code review processes

• Identify process inefficiencies and technical debt limiting engineering productivity

• Improve delivery practices through pragmatic, incremental change rather than large-scale transformation programmes

• Enable delivery teams to adopt AI-assisted development safely and effectively

• Remove barriers such as:

  • Slow feedback loops
  • Manual approval bottlenecks
  • Poor branching discipline
  • Inconsistent environments
  • Inefficient release processes

• Work closely with stakeholders to build trust and drive adoption of improved engineering practices

• Capture recurring themes and opportunities for platform-wide improvements

• Measure and report on outcomes including cycle time improvements, review turnaround times, deployment efficiency, and delivery performance

Essential Skills

• Strong DevOps and Software Delivery Lifecycle (SDLC) experience
• CI/CD pipeline design and optimisation
• Branching strategy and source control governance
• Release and environment management
• Experience reviewing and improving existing engineering processes
• Ability to work directly with delivery teams to understand current-state processes
• Strong stakeholder engagement and change adoption skills
• Understanding of how engineering processes impact AI-assisted software delivery
• Experience with GitLab, Jira, Confluence, or equivalent enterprise toolsets

Desirable Skills

• Experience with AI-assisted development tools such as GitHub Copilot or similar code assistants
• Exposure to agentic development workflows and AI-driven engineering practices
• Process improvement or change management background
• Experience working within regulated, public sector, or government environments

What We're Looking For

Candidates who understand that successful AI adoption is not simply about introducing new tools. It requires strong engineering foundations, efficient delivery processes, and the removal of process debt that prevents teams from realising the benefits of modern AI-assisted software development.