Data Scientist, LLM (AI Agent)

Responsibilities:

• Responsible for the architecture design and core module development of LLM-based AI Agent systems, including task planning, memory management, tool invocation, and workflow execution;
• Lead the development of a general-purpose Agent platform capable of multi-task coordination and multi-agent collaboration, enhancing the usability and stability of large models in complex business scenarios;
• Leverage key technologies such as LLMs, RAG, vector search, and function calling to build intelligent systems with contextual understanding and knowledge injection capabilities;
• Develop evaluation systems and automated testing tools for Agent behavior to continuously optimize task completion rate, response quality, and reliability;
• Drive the application of AI Agents in vertical scenarios such as search, trading, deep analysis, and automated data engineering to unlock the full value of LLMs.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Financial Engineering or a related discipline
• Solid understanding of LLM principles (e.g., Transformers) and their application in Agent systems, with end-to-end experience in building and launching intelligent agents;
• Proficiency in at least two mainstream open-source Agent frameworks such as LangChain, AutoGen, LangGraph, ADK, LlamaIndex, Dify, CrewAI, or CAMEL, with a strong grasp of their internal architectures;
• Familiar with RAG (Retrieval-Augmented Generation) and capable of designing and optimizing knowledge retrieval systems; experience with vector databases like Milvus or FAISS is required;
• Experience implementing key Agent modules including Tool Use, Task Planning, Memory Management, and understanding their integration in real-world applications;
• Strong software engineering background, proficient in Python/Java, and familiar with client-server architectures and MCP-like communication protocols.