Senior Java Engineer - AI/GenAI
Remote (South Cambridgeshire) · Staff/Principal · Remote
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What we know about this role
HIGH
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First 72 hours
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Skills required
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Job description
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
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