Senior Java Engineer - AI/GenAI

About the job Job Title - Senior Java Engineer Location - Poland 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