Java Developer – AI-Enabled Delivery

Technologies we use

About the project

Your responsibilities

• Engineering Delivery:
• Design, build, test, and release Java microservices using Spring Boot for enterprise-scale platforms.
• Contribute to architectural discussions and solution design, ensuring alignment with non-functional requirements (performance, resilience, scalability).
• Help resolve technical risks, dependencies, and blockers across multiple workstreams.
• AI-Enabled SDLC & Engineering Governance:
• Use AI-assisted tools responsibly to accelerate development cycles while applying governance and guardrails for security, IP control, and compliance.
• Apply GenAI techniques such as LLM-assisted development and prompt engineering under strict controls.
• Contribute to safe usage patterns for retrieval-augmented generation (RAG) and agent-based workflows with human-in-the-loop validation.
• Quality, Security & Operational Readiness:
• Implement unit, integration, and contract tests with strong coverage metrics (JUnit, Mockito, TestContainers).
• Ensure secure coding practices, vulnerability management, and observability (logs, metrics, traces).
• Deliver production-ready services supporting reliability and compliance requirements.
• Collaboration:
• Work closely with Tech Leads, QA, SRE, architects, and platform teams to integrate microservices across business-critical systems.
• Foster a culture of continuous improvement and inclusive team collaboration.
• Note: Detailed project information will be shared during the recruitment process.

Our requirements

• 4–8 years’ experience in software engineering with strong background in:
• Building Java microservices (Spring Boot) in enterprise environments.
• RDBMS design and optimization (Oracle/PostgreSQL).
• Integration patterns (REST, messaging/eventing) and API versioning strategies.
• CI/CD pipelines and tooling (Jenkins/GitLab, Sonar, SAST/DAST).
• Strong test automation experience (JUnit, Mockito, TestContainers).
• Hands-on experience with cloud (GCP) deployment models.
• Familiarity with GenAI concepts, LLM use cases, RAG/agent-based patterns, and governance principles.
• Ability to make pragmatic decisions under tight deadlines while maintaining quality standards.

Optional

• Exposure to regulated financial services environments with strict controls.
• Experience with containerized deployment, Kubernetes, and modern observability stacks.
• Prior work implementing AI-enabled SDLC practices responsibly with governance.
• Hands-on GenAI prototyping: RAG pipelines, evaluation approaches, prompt/version management.

What we offer

• Flexible cooperation model
• Hybrid work setup – 8 days per month in the office in Kraków - remote days available depending on the client’s arrangements
• Collaborative team culture – work alongside experienced professionals eager to share knowledge
• Continuous development – access to training platforms and growth opportunities
• Comprehensive benefits – including Interpolska Health Care, Multisport card, Warta Insurance, and more
• High quality equipment – laptop and essential software provided

This is how we work on a project

Benefits