Engineering Manager - DevOps & AI Platform

Built trust across both functions and their counterparts, and developed a clear, evidence-based picture of the platform's reliability and cost posture and of how the AI Platform centre of excellence currently works and shares knowledge.

Shaped and begun executing a people and hiring strategy across both functions, growing DevOps toward its target and building out the AI Platform and AI infrastructure team.

Begun operating as an effective conduit for the centre of excellence, strengthening how agent-building best practice, MCP and evaluation approaches are defined centrally and adopted by product teams.

Established a clear point of view on AI SDLC and how the platform enables it, and championed SRE practices across the business.

Lead through people: you measure your success by the growth and impact of your team, not your own output.

Are credible with senior engineers without needing to be the hands-on expert: you ask the sharp question and facilitate the right decision.

Are genuinely curious about AI, agents and evaluations, and energised by helping an organisation learn to build with them well.

Are honest and pragmatic about timelines and trade-offs, and comfortable owning a long-term build-out across two functions.

Care about the mission: providing the infrastructure and intelligence that keep financial institutions safe from crypto crime and sanctions evasion.

A track record of managing DevOps, platform or infrastructure engineers, including hiring and building a growing team.

An infrastructure background (cloud, IaC, CI/CD, observability) deep enough to make sound strategic calls and guide senior engineers toward the right ones.

Extreme curiosity about AI and budding hands-on experience with AI, agents and evaluations: not necessarily deep expertise, but a real, demonstrated pull toward the space and the judgement to grow into leading it.

A strong interest in the nuances of the AI-assisted SDLC, and the conviction that tooling alone does not make engineers more potent. Adoption, practice and guardrails are what turn AI access into real leverage.

Kubernetes literacy, grounded in hands-on experience as an engineer, sufficient to reason about the estate and challenge the team's decisions.

AI fluency: candidates must be able to demonstrate practical, responsible use of AI in an engineering context and the ability to set team norms for it. We are looking for an active AI promoter who can reason about where AI adds leverage and where it is a liability in a compliance setting.

Experience leading or building an internal platform, ML platform, developer-experience or enablement function.

Hands-on exposure to agent frameworks, MCP, or building and running evaluation frameworks.

Experience of a company scaling phase.

Exposure to ISO 27001 / SOC2 and what they demand of infrastructure and process.

Experience with high-throughput, low-latency systems in a regulated or financial context.

HODLs Crypto.

Hybrid working and the option to work from almost anywhere for up to 90 days per year

£500 Remote working budget to set up your home office space

$1,000 Learning & Development budget to use on anything (agreed with your manager) that contributes to your growth and development

Holidays: 25 days of annual leave + bank holidays

An extra day for your birthday

Enhanced parental leave: we provide eligible employees, regardless of gender or whether they become a parent by birth or adoption, 16 weeks fully-paid leave and leave.