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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