We are seeking an experienced AI Agent Development Engineer with automotive industry expertise to join our automotive software R&D team. As a core member, you will be responsible for developing AI agent applications based on large language models, designing and implementing AI solutions for automotive business scenarios, and ensuring efficient and reliable integration of agent systems. Your expertise will directly contribute to the intelligent transformation of the automotive industry and drive the continuous improvement of automotive software AI application systems。
Agent Application Development and Integration:
Agent Application Design and Development: Responsible for developing AI agent applications based on privately deployed open-source large language models (such as DeepSeek, Qwen, etc.), including conversational assistants, knowledge Q&A and analysis Agents, and code generation Agents to meet automotive business scenario requirements.
Agent Framework Application and Optimization: Proficient in using Agent frameworks such as LangChain, LangGraph, DeepAgents, etc., to complete tool orchestration, RAG, memory management, and multi-Agent collaboration, improving development efficiency and system performance.
Automotive Business Scenario AI Integration:
Automotive Business Process Intelligence: Integrate AI agents with existing automotive development systems (such as SystemWeaver, etc.) to implement automated or semi-automated development processes and improve development efficiency.
Agent Core Architecture Design and Implementation: Design and implement LLM-based agent core architectures, including task planning, intent recognition, and workflows. Master Skills management, MCP protocol, Subagent context management mechanisms and apply them proficiently.
Agent Backend Services and API Development: Design and implement agent-related backend services and APIs, including task scheduling, access control, logging, monitoring, and alerting to ensure stable system operation.
Agent Performance Optimization and Iteration: Optimize agent performance, including Prompt tuning, retrieval strategy optimization, model parameter configuration, and stability optimization. Continuously track AI agent application effectiveness and adjust workflows and iterate applications based on business feedback.
Service Resource Requirements:
Education and Experience: Bachelor's degree or higher in Computer Science, Artificial Intelligence, Software Engineering, or related fields. 1+ years of experience in AI agent development, familiar with large language model application development. Automotive industry experience is preferred.
Agent Technology Stack: Proficient in Agent development frameworks such as LangChain, LangGraph, DeepAgents, etc., capable of building scalable agent systems. Familiar with Skills management, MCP (Multi-Agent Communication Protocol) protocol, Subagent context management mechanisms. Possess Client-Server architecture development and integration capabilities, able to design efficient Agent communication mechanisms.
Technical Skills: Proficient in Python programming language, familiar with web frameworks (Flask, FastAPI, Django, etc.), API design, concurrency/asynchronous programming, caching, message queues, etc. Experience with large language model APIs, understanding of tool calling, RAG, and Prompt design. Familiar with vector databases (Weaviate, Chroma, Pinecone, Milvus, etc.) and memory management frameworks (MemGPT, LangMem, Zep, etc.).
Engineering Excellence: Strong logical thinking and problem-solving skills, able to quickly identify and resolve technical issues.
Collaboration Skills: Efficient cross-functional team communication skills, strong documentation writing skills, able to build agent applications and implement automated processes in automotive business scenarios. Collaborate with AI agent product managers to implement agent solutions into runnable systems.
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