R&D Engineer - Expert

1. Enhance R&D efficiency through AI technology application and implementation

2. AI Application Development and Project Delivery

• Lead AI project requirements analysis, technical solution design, and product delivery
• Complete fine-tuning, alignment, and inference optimization for general models, embedded models, and inference models
• Build efficient and usable Prompt Engineering workflows to improve model task performance

3. Multi-Agent Systems and Framework Applications

• Implement multi-agent workflow orchestration using frameworks like LangChain, LangGraph, and MCP
• Design and implement key reasoning paradigms (ReAct, CoT, ToT) to improve agent system responsiveness and controllability
• Understand agent platforms such as Coze, FastGPT, and Dify

4. Knowledge Retrieval and RAG Systems

• Build document knowledge retrieval systems based on vector databases (Milvus, FAISS, Chroma, etc.)
• Design RAG architecture solutions to enable context-enhanced interactions with large language models (e.g., ChatGPT, DeepSeek)
• Improve document recall quality and reasoning relevance

5. Technical Research and Capability Development

Track AI technology trends (model alignment, multimodality, multi-agent systems, etc.), regularly complete technical research, develop application prototypes, or deliver technical presentations