Software Developer (AI)

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.]]> 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

]]> 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)]]> 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 

]]>