Responsibilities
- Design and implement LLM-powered and agent-based solutions, including RAG pipelines and knowledge retrieval systems.
- Build and orchestrate AI agents using Python and Gemini.
- Design document ingestion pipelines (chunking, embeddings, metadata enrichment).
- Integrate vector databases and internal data sources.
- Define prompt engineering strategies and evaluate LLM outputs.
- Ensure enterprise-grade security, governance, and compliance.
- Act as architect and technical lead, setting standards and guiding delivery from POC to production.
Required Qualifications
- Hands-on experience building LLM and RAG-based applications.
- Strong Python skills (production-grade code).
- Experience with Gemini or other enterprise LLMs.
- Knowledge of vector databases (FAISS, Weaviate, Pinecone, or similar).
- Solid understanding of NLP (entity extraction, summarization, classification).
- Experience with prompt engineering and agent workflows.
We offer
- B2B contract,
- Daily support from team leaders,
- Dedicated certification budget,
- Assistance in defining and support in your development path,
- Benefits package,
- Integration trips/events.
Benefits
-
Integration events
-
Private medical care (Luxmed or PZU)
-
Life insurance (Unum or PZU)
-
Sports card Multisport
-
Employee referral programs
-
Psychological support
-
Offices in Warsaw and Łódź
-
English language classes
-
Budget for technical certificates
-
Discount on Orange products
-
Co-financing of boat trips