Participate in the design and core module development of enterprise-level AI Agent systems (e.g., dialogue management, task planning, multimodal interaction).
Integrate technologies such as RAG, knowledge graphs, and vector databases to optimize task execution efficiency and resource consumption.
Develop intelligent agent workflows to enhance capabilities in autonomous decision-making, tool calling, and multi-agent collaboration (e.g., ReAct, Chain-of-Thought).
Technical Research & Innovation
Stay abreast of cutting-edge AI Agent technologies (e.g., AutoGPT, Model Context Protocol, Reinforcement Learning) and drive their implementation in engineering scenarios.
Requirements
QualificationsHard Skills
Bachelor's degree or higher in Computer Science, Artificial Intelligence, or a related field.
Solid foundation in data structures and algorithms.
Practical experience in development with Python or Java.
Familiarity with mainstream frameworks such as LangChain, LlamaIndex, and AutoGen.
Experience with vector databases (e.g., Milvus), knowledge graphs, and multi-source data fusion solutions.
Soft Skills
Strong logical thinking and ability to independently solve problems, capable of owning the full development lifecycle from design to deployment.
Excellent team player with effective communication skills.
Passion for LLM technology, with a strong capacity for rapid learning and innovation.
