Senior Java Engineer - AI/GenAI

• 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

• 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