About the job
Job Title - (AI-First) Senior Java Engineer
Location - London Area, United Kingdom (Hybrid)
Years of experience - 8+ years of experience
What you'll need for this role
Backend Engineering
* 8+ years software engineering with Java backend expertise
* Experience modernising production systems at scale
* Strong API design and microservices architecture knowledge
* Understanding of strangler fig patterns, service decomposition, and legacy migration strategies
AI/LLM Implementation (Critical Differentiator)
* Hands-on experience building with Model Context Protocol (MCP)
* Demonstrated use of Claude Code, GitHub Copilot, or similar AI development tools in production work
* Experience implementing AI in CI/CD pipelines (code review, testing, security scanning)
* Built agentic AI solutions or AI-powered automation tools
* Understanding of prompt engineering, model selection, and LLM
capabilities/limitations
Proven AI Impact
* Achieved measurable productivity improvements using AI in development
* Implemented AI-assisted refactoring, test generation, or documentation at scale
* Experience with AI code analysis and automated remediation
* Track record of shipping production systems built with AI assistance
What you'll do
Service Modernisation (50%)
Modernise Legacy Services Using AI
* Use AI to analyse codebases, understand dependencies, and extract clean APIs
* Work on high-impact legacy services that block divisional delivery speed
* Implement strangler fig patterns and other proven migration approaches
* Deliver modernised services with comprehensive tests, documentation, and multi-instance deployment capabilities
Ship Results Quickly
* Complete service modernisations in fast cycles with monthly milestones
* Use AI to accelerate every phase: analysis, refactoring, testing, documentation
* Hand off modernised services to Platform Services or divisions with clear ownership
* Demonstrate measurable improvements: faster APIs, better performance, higher reliability
AI Implementation & Automation (50%)
* Build AI-Powered Development Infrastructure
* Implement Model Context Protocol (MCP) servers for service discovery, dependency mapping, and architecture compliance
* Create AI-assisted CI/CD pipelines with automated code review, security scanning, and test generation
* Build automation using Claude Code, GitHub Copilot, and LLM APIs
* Develop reusable AI tooling that other engineers can adopt
Demonstrate AI-First Development
* Use AI for all coding tasks: refactoring, test creation, documentation, debugging
* Achieve measurable and significant productivity improvements through AI integration
* Document patterns and share learnings through your work
* Train teams during service handoffs on AI-enabled workflows you've built
* Demonstrate when to use AI vs when human judgement is critical