This position is not available in GPP database. Talent Acquisition team member will fill in the Posting description after intake meeting.

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This position is not available in GPP database. Talent Acquisition team member will fill in the Posting description after intake meeting.

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AI Intern – RAG Engineering

Job Summary

You will participate in the engineering development and optimization of enterprise‑level RAG systems, focusing on key areas such as knowledge processing, retrieval strategies, and context construction to support stable AI system operation in real business scenarios. You will be involved in the full engineering workflow, from document processing to RAG performance optimization.

Key Responsibilities

• Participate in foundational engineering work for RAG systems, including document processing, knowledge organization, and testing;
• Assist with document parsing, text chunking, and basic data cleaning;
• Participate in testing and analysis of retrieval results, and help optimize retrieval quality and context construction;
• Build and validate RAG application prototypes using platforms such as Dify;
• Support experiments and validation of RAG systems in specific business scenarios;
• Write basic technical documentation;

Qualifications & Skills

• Undergraduate or graduate student in Computer Science, Data Science, Artificial Intelligence, or a related field;
• Familiar with Python or another common programming language;
• Familiar with the basic principles and core workflow of RAG, including key stages such as document processing, text chunking, retrieval, and context construction;
• Familiar with text processing methods, and have exposure to common LLM / Agent application frameworks or platforms such as LangChain, LangGraph, and Dify;
• Project or hands‑on experience is a plus (e.g., chatbots, text generation, or question‑answering systems);
• Strong learning ability and problem‑solving skills; able to progressively work independently under guidance;
• Good communication skills and teamwork spirit, able to collaborate effectively with team members;