Key skills
AWSDockerElasticSearchJavaSpringSpring BootSpringBootAILLMOpenAIAnthropicRAGQdrantPineconeMilvusBedrockElasticsearchDecision MakingCollaboration
About this role
Role Overview
- 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
- 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)
Tech Stack
- AWS
- Docker
- ElasticSearch
- Java
- Spring
- Spring Boot
- SpringBoot
Benefits
- Professional development
- Collaboration with the Team Lead and Product Owner