Agent Application Development - LLM Track

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Opis

About the role We are looking for an engineer specialized in LLM Agent systems. You will own the design, prototyping and production deployment of autonomous agents, multi-agent workflows, tool calling pipelines and grounded RAG systems. Key responsibilities Design and implement LLM agent architectures: task planning, tool use, long-term memory, state management and human-in-the-loop workflows with frameworks such as LangGraph, AutoGen, CrewAI Build and optimize RAG pipelines: document parsing, vector retrieval, grounding, hallucination mitigation and evaluation metrics Conduct prompt engineering, supervised fine-tuning, and develop automated benchmarks for agent capability (GAIA, SWE-bench style evaluation) Build backend services, agent sandbox environment, API orchestration, deployment monitoring and failure tracing Track cutting-edge agent research (reflection, multi-modal agents, A2A protocol), run PoCs and deliver technical reports Collaborate with the AI evaluation team to design agent test suites and automated assessment pipelines About you PhD in Computer Science, AI, NLP or Machine Learning preferred Publications in top conferences (NeurIPS, ICLR, ACL, ICML) are a big plus Solid theoretical foundation in LLMs, NLP, machine learning, alignment and context engineering Proficient in Python; hands-on production experience building agents with LangGraph, AutoGen, LlamaIndex and vector databases (Milvus, Pinecone, Chroma) Proven experience in tool-calling, multi-agent colla

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