Lead AI Engineer with Java 17

We are searching for a Lead AI Engineer who is truly AI-native and prepared to deliver hands-on technical leadership of a delivery squad. This isn't a position for conventional engineers who have merely added AI tools on top of old routines - we require a leader who codes daily, owns architecture, upholds standards, and treats AI-assisted delivery as the core engineering model (targeting 60%+ AI-assisted code output). You will mentor engineers, shape specifications, and collaborate with client architects and leadership across both Agile and project delivery modes.

Responsibilities Deliver hands-on technical leadership of a delivery squad while actively writing code Own end-to-end architecture within the squad and lead architecture discussions with client architects Drive specification quality, enforce engineering standards, and stay accountable for delivery quality and governance Apply AI coding tools (such as Claude Code, GitHub Copilot, or Cursor) daily for generating, refactoring, testing, and reviewing code - reaching 60%+ AI-assisted code output Configure MCP servers, implement multi-agent patterns, and set up AI/LLM gateways to manage routing, cost, limits, and fallbacks Leverage AI to assess agent output quality and continuously refine 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 needed to support squad delivery Present progress, architecture, and AI adoption outcomes to senior leadership Mentor teams on AI adoption and champion 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 Proven 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 Demonstrated 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