Senior Java Developer - AI

Antal is a leading recruitment and HR advisory company, present in Poland since 1996 and later expanded to the Czech Republic and Hungary. Across the CEE region, they employ around 150 professionals delivering specialist and executive recruitment, employee outsourcing, HR consulting, employer branding, and market research. Their division-based structure combines deep industry expertise with functional specialisation, providing tailored solutions for companies in every sector.

• Strong hands-on experience building Java microservices using Spring Boot
• Solid experience with RDBMS such as Oracle and PostgreSQL
• Strong unit and integration testing practices using JUnit, Mockito, and Testcontainers
• Experience with CI/CD pipelines and quality gates using Jenkins or GitLab, Sonar, SAST, and DAST
• Good understanding of integration patterns including REST and messaging/eventing
• Experience contributing to technical design and making pragmatic trade-offs
• Hands-on experience with Google Cloud Platform (GCP)
• Practical exposure to Generative AI concepts and engineering tooling
• Familiarity with RAG and agent patterns and governance

Nice to Have:

• Experience delivering regulated financial services platforms
• Exposure to cloud-native patterns such as containers, Kubernetes, and service mesh
• Experience with performance engineering and resilience testing
• Experience implementing AI-enabled SDLC practices

• Build, test, release, and support Java microservices
• Contribute to solution design aligned with architecture and non-functional requirements
• Identify and resolve technical risks, dependencies, and delivery blockers
• Follow engineering standards including coding, branching, CI/CD quality gates, and test strategy
• Deliver unit, integration, and contract tests with measurable coverage
• Participate in design, code, and security reviews
• Use AI-assisted tooling responsibly to accelerate delivery
• Apply guardrails for AI-generated code such as reviews, secure coding, and traceability
• Use GenAI techniques where appropriate including LLMs, prompt engineering, and validation
• Contribute to GenAI-enabled patterns like LLMs, RAG, and agent workflows
• Embed security-by-design and vulnerability management
• Build production-ready services with observability and performance readiness
• Support release activities, integration, and environment preparation
• Collaborate with Tech Leads, QA, SRE, architects, and platform teams