AI / LLM Engineer

Nasze wymagania: You've built something with LLMs that actually runs in production — doesn't matter if it was at a big company or a side project Solid Python skills — not scripts, but clean code you're not ashamed of Working knowledge of RAG: you understand why naive chunking fails and what to do about it Experience with at least one agent framework (LangChain, LlamaIndex, LangGraph) Familiarity with vector databases (Qdrant, Weaviate, Pinecone, pgvector — any) You know how to ship: REST APIs, Docker, cloud basics (AWS / Azure / GCP) English B2+ — client-facing role, calls and written communication included Mile widziane: Experience evaluating LLM outputs (RAGAS, LangSmith, Arize or similar) MLflow or another experiment tracking tool Databricks, Azure AI Foundry or AWS Bedrock Fine-tuning experience (LoRA, PEFT, anything hands-on) Kafka or streaming pipelines for real-time AI use cases O projekcie: We're looking for an engineer who genuinely gets excited about building things with AI — someone who shipped something real with LLMs, not just played with the API. You'll work on international projects for clients in banking, insurance, and telco (US, Netherlands, UK), translating messy business problems into working AI systems. You don't need 10 years of "AI experience" — this field is too new for that. What matters is that you think clearly, learn fast, and can take an idea from whiteboard to production. Zakres obowiązków: Building LLM-powered applications and RAG systems for enterprise clients Designing and implementing AI agents (LangChain, LangGraph, CrewAI or similar) Integrating LLMs (OpenAI, Anthropic, Gemini, open-source) into existing systems Building data ingestion pipelines: chunking, embedding, vector indexing Writing production-grade Python code — APIs, tests, containers, the full stack Working directly with clients: understanding their requirements, presenting solutions Doing code reviews, writing docs, contributing to team engineering standards Oferujemy: Certifications and training funded Private medical care (Medicover) Multisport card English language classes Flexible working hours Team meetups and integration events Referral bonus