Software Developer (AI)

We are looking for an experienced Java Developer with strong technical skills and a passion for creating high-quality, clean, and maintainable code. The ideal candidate has at least 3 years of professional experience and a solid background in backend development using modern Java technologies.
The perfect fit is a team-oriented person who values collaboration, knowledge sharing, and collective problem-solving. A genuine interest in data and databases is highly appreciated. We are looking for an experienced Java Developer with strong technical skills and a passion for creating high-quality, clean, and maintainable code. The ideal candidate has at least 3 years of professional experience and a solid background in backend development using modern Java technologies.
The perfect fit is a team-oriented person who values collaboration, knowledge sharing, and collective problem-solving. A genuine interest in data and databases is highly appreciated.
  • DesigningandimplementingAIagentswithreasoningpipelines(e.g. multi-stepworkflows,toolusage, RAG-baseddecisionmaking)
  • IntegratingAIcapabilitiessuchasLLM-poweredservices,semanticsearch, and intelligentautomation
  • Contributingtoscalablearchitecturesfordata- and event-drivensystems
  • Improving, refactoring, andmaintainingexistingcodebases
  • DesigningtasksincollaborationwiththeTeam Lead andProductOwner
  • Participatingin codereviews,architecturediscussions, andknowledgesharing
  • Contributed to the design of scalable architectures for data-heavy and AI-drivenservices
  • CollaboratecloselywiththeTeam Lead andProductOwnertodesigntasksandshapetechnicalsolution
  • Participatein codereviews,architecturediscussions, andknowledge-sharingsessions
Java
Spring Boot / Spring AI
Docker
AI-related:
  • Experience integrating LLMs into applications (OpenAI API, Anthropic, local inference, etc.)
  • Understanding of vector databases (Milvus, Pinecone, Qdrant, Elasticsearch vector search, or similar)
Polish – C1 (required)
English – C1/B2+ (required) Redis
Mongo DB
AI-related:
  • Knowledge of embeddings, prompt engineering basics, and retrieval-augmented generation (RAG)
  • Experience with AI/ML frameworks or orchestration libraries (LangChain4j, Spring AI, Embabel, Haystack, etc.)
  • Familiarity with LLM model lifecycle: prompt design, evaluation, latency considerations, cost/performance trade-offs
  • Experience with Ollama / vLLM
  • Experience with streaming architectures for AI pipelines (i.e. Kafka Streams)
  • Experience with document processing, OCR, or semantic search

See also

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