LLM Developer

Wymagania: - Strong hands-on Python development (mandatory).- Experience with GenAI frameworks (LangChain, LangGraph, CrewAI).- Deep understanding of agentic reasoning, orchestration, and tool integration.- Experience with Azure AI Foundry and Azure OpenAI.- Familiarity with vector databases (Azure AI Search, Pinecone, Weaviate, OpenSearch).- Understanding of tokenisation, context windows, rate limits, and cost optimisation.- API integration, async programming, and resilient error handling patterns.- Strong knowledge of Responsible AI risks and mitigation.- Other Requirements:- Production-first mindset (observability, resilience, scalability).- Ability to balance innovation with compliance and safety.- Strong documentation and architectural communication skills. Codzienne zadania: - Design and implement end-to-end GenAI solutions using Python. - Build agentic workflows using frameworks such as LangGraph, tool/function calling, MCP, and multi-agent orchestration. - Develop robust RAG pipelines including ingestion, chunking, embeddings, vector search, re-ranking, and grounding validation. - Implement memory strategies (short-term, long-term, summarised, vector-based memory). - Integrate and evaluate multiple LLM models (e.g., GPT-4.x series, GPT-4o). - Develop structured output and tool-calling systems with schema enforcement. - Build evaluation frameworks covering hallucination detection, quality scoring, latency, and cost metrics. - Implement Responsible AI guardrails including input/output filtering and fallback strategies. - Collaborate with DevOps/LLMOps teams for deployment, monitoring, scaling, and cost optimisation.