Lead AI Engineer with Java 17

We are seeking a Lead AI Engineer who is genuinely AI-native and ready to drive hands-on technical leadership of a delivery squad. This is not a role for traditional engineers who have simply layered AI tools on top of old habits — we need a leader who writes code daily, owns architecture, enforces standards, and uses AI-assisted delivery as the core engineering model (targeting 60%+ AI-assisted code output). You will coach engineers, shape specifications, and partner with client architects and leadership across both Agile and project delivery modes. Responsibilities Provide hands-on technical leadership of a delivery squad while actively contributing code Own end-to-end architecture within the squad and lead architecture discussions with client architects Drive specification quality, enforce engineering standards, and remain accountable for delivery quality and governance Use AI coding tools (such as Claude Code, GitHub Copilot, or Cursor) daily for generating, refactoring, testing, and reviewing code — achieving 60%+ AI-assisted code output Configure MCP servers, apply multi-agent patterns, and set up AI/LLM gateways to manage routing, cost, limits, and fallbacks Leverage AI to evaluate agent output quality and continuously improve delivery practices Coach engineers on prompts, context management, and skill files, and review and approve skill-file contributions Step into any full-stack or mobile role as required to support squad delivery Present progress, architecture, and AI adoption outcomes to senior leadership Mentor teams on AI adoption and promote AI-native ways of working across the delivery organisation Requirements 12-15 years of overall engineering experience, including 3+ years leading AI-assisted delivery teams Track record of leading delivery in a regulated sector (financial services preferred), with references available Background in Java 17+ and Spring Boot 3.x (mandatory) with microservices architecture Expertise in frontend development with React (mandatory), TypeScript, and component design Proficiency in responsive UI development and Figma-to-code workflows Skills in REST and event-driven APIs, OAuth2 / OIDC, and PostgreSQL Competency in messaging platforms, including Kafka and IBM MQ Capability to own service pipelines using GitHub Actions, Docker, and Kubernetes / OpenShift Qualifications in GitOps practices and automated testing Showcase of leading at least one programme where AI-assisted delivery was the primary engineering model (not a pilot) Familiarity with MCP server configuration, multi-agent patterns, and AI/LLM gateway configuration Proven ability to mentor teams on AI adoption and work comfortably across both Agile and project modes English proficiency at an Upper-Intermediate level (B2) or higher