Senior Java Engineer – AI/GenAI

This is a fully remote position, open to applicants in Poland.

📋 Description

• Revamp Legacy Services Utilizing AI

• Employ AI to analyze codebases, comprehend dependencies, and extract streamlined APIs

• Focus on impactful legacy services that hinder divisional delivery efficiency

• Apply strangler fig patterns alongside other established migration techniques

• Produce modernized services equipped with thorough tests, documentation, and multi-instance deployment functionalities

• Complete service modernizations in rapid cycles with monthly targets

• Leverage AI to expedite every stage: analysis, refactoring, testing, documentation

• Transition modernized services to Platform Services or divisions with clearly defined ownership

• Exhibit quantifiable enhancements: expedited APIs, improved performance, and increased reliability

• Establish AI-Driven Development Infrastructure

• Implement Model Context Protocol (MCP) servers for service discovery, dependency mapping, and architectural compliance

• Develop AI-assisted CI/CD pipelines featuring automated code reviews, security assessments, and test generation

• Create automation using Claude Code, GitHub Copilot, and LLM APIs

• Design reusable AI tools that can be adopted by other engineers

• Utilize AI for all coding responsibilities: refactoring, test creation, documentation, and debugging

• Attain measurable and significant productivity enhancements through AI integration

• Document methodologies and disseminate insights gained from your work

• Educate teams during service transitions on the AI-enabled workflows you have developed

• Illustrate when to deploy AI versus when human judgment is essential

⛳️ Requirements

• 8+ years of experience in software engineering with a focus on Java backend development

• Experience in modernizing production systems on a large scale

• Solid knowledge of API design and microservices architecture

• Understanding of strangler fig patterns, service decomposition, and legacy migration strategies

• Practical experience in building with Model Context Protocol (MCP)

• Proven utilization of Claude Code, GitHub Copilot, or comparable AI development tools in production environments

• Experience in implementing AI within CI/CD pipelines (code reviews, testing, security scans)

• Developed agentic AI solutions or AI-driven automation tools

• Knowledge of prompt engineering, model selection, and the capabilities/limitations of LLMs

• Demonstrated measurable productivity enhancements achieved through AI in development

• Implemented AI-assisted refactoring, test generation, or documentation at scale

• Experience with AI code analysis and automated remediation

• Proven history of deploying production systems enhanced by AI assistance.

🏝️ Benefits

• Options for remote work