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Tech Stack
Tools & technologiesAWSDockerElasticSearchJavaSpringSpring BootSpringBoot
About the role
Key responsibilities & impact- Designing and implementing AI agents with reasoning pipelines (e.g., multi-step workflows, RAG-based decision making)
- Integrating AI capabilities such as LLM-powered services, semantic search, and intelligent automation
- Contributing to scalable architectures for data- and event-driven systems
- Improving, refactoring, and maintaining existing code bases
- Designing tasks in collaboration with the Team Lead and Product Owner
- Participating in code reviews, architecture discussions, and knowledge sharing
Requirements
What you’ll need- 5+ years of professional experience
- Java
- Spring Boot
- Docker
- AI-related: Spring AI
- Experience integrating LLMs into applications (OpenAI API, Anthropic, local inference, etc.)
- Understanding of vector databases (Milvus, Pinecone, Qdrant, Elasticsearch)
- AWS Bedrock
- LangChain4j
- Knowledge of embeddings, prompt engineering basics, and retrieval-augmented generation (RAG)
- Understanding Model Context Protocol
- Polish – C1 (required)
- English – C1/B2+ (required)
Benefits
Comp & perks- Professional development
- Collaboration with the Team Lead and Product Owner
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI Agent DesignMulti-Step WorkflowsRAG-Based Decision MakingCode RefactoringPrompt EngineeringVector DatabasesEmbeddings KnowledgeModel Context Protocol
