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Open nowPosted 150 days ago

Senior Java Engineer - AI/GenAI

RemoteStar90 open roles

Where
Cambourne, United Kingdom of Great Britain and Northern Ireland, Remote
Work mode
Remote
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Your applicationOpen nowSenior Java Engineer - AI/GenAIRemoteStar · Cambourne, United Kingdom of Great Britain and Northern Ireland, Remote

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 150 days ago

The posting

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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