Summary
✨ AI‑Generated
A DevOps process leader is needed to improve software delivery practices, optimize CI/CD workflows, and enable efficient engineering operations across delivery teams.
Highlights
Lead improvements in engineering processes and help teams adopt scalable AI-ready delivery practices.
Description
We are building an enterprise-grade AI platform to enable secure, scalable and production-ready use of Generative AI and ML across the Customs Declaration Service.
Location: Anywhere in the UK, with the option to attend the office when required.
Mandatory
Strong DevOps/SDLC background, CI/CD pipeline design, branching strategy, release management and environment managementExperience assessing and improving existing engineering processes within a delivery team, not just building new pipelines from scratchStakeholder engagement, able to work embedded with delivery teams to understand current-state process, build trust and land changeUnderstanding of what "AI-ready" DevOps looks like, e.g.
how process friction, slow CI, manual gates and poor branch hygiene, blocks AI coding assistants and agentic workflows from adding valueFamiliar with common CDS delivery toolchain, GitLab, JIRA, Confluence or equivalent enterprise DevOps tooling
Nice to Have
Experience with AI-assisted development tooling, Copilot-style code assistants, agentic PR workflows and what they need from surrounding process to work wellChange management / process consulting backgroundExposure to regulated/government delivery environments
Key Responsibilities
The DevOps/Process Change role works directly with CDS delivery teams to understand their existing DevOps processes, identify process debt, and address it so those teams can get genuine value from AI-assisted delivery, not applying AI on top of broken process and expecting it to compensate.
Embed with individual CDS delivery teams to assess current DevOps practice, CI/CD, branching, release cadence, testing gates and review processIdentify process debt that limits the value of AI coding/delivery tools, e.g.
slow feedback loops, manual approval bottlenecks and inconsistent environment managementWork with teams to remediate process debt in a practical, incremental way, not a big-bang process overhaulAdvise teams on how to structure process so AI-assisted development, code assistants and agentic workflows, can be adopted safely and effectivelyFeed findings back to the platform team on recurring cross-team process patterns worth solving once, platform-wide, rather than team-by-teamTrack and report on process improvement outcomes per team, e.g.
cycle time and review turnaround, to evidence the debt-paydown case
