滴滴高级/资深 agent研发工程师(JR2026042200S)
社招全职3年以上技术地点:北京状态:招聘
工作描述
任职要求
1、基本要求:具备3年以上工作经验,其中包含至少2年以上 AI 研发工作经验
2、技术能力:
2.1 精通主流 Agent 开发框架(如 LangChain / LangGraph、CrewAI、AutoGen、Dify、Coze等),具备框架选型与深度定制能力
2.2 精通记忆管理与上下文工程,熟悉对话状态管理、滑动窗口、摘要压缩、长期记忆持久化等核心技术方案
2.3 精通 RAG 技术全链路,包括文档解析、分块策略、Embedding模型选型、向量数据库的搭建与调优,以及检索增强生成的效果优化
2.4 熟悉主流大模型(GPT、Claude、GLM开源模型等)的能力边界与 Prompt Engineering最佳实践
2.5 具备扎实的后端开发能力,熟练掌握 Python/TypeScript 至少一门语言
3、项目经验
3.1 具备实际 Agent 项目…登录查看完整工作描述
微信扫码,1秒登录
包括英文材料
AI agent+
https://www.ibm.com/think/ai-agents
Your one-stop resource for gaining in-depth knowledge and hands-on applications of AI agents.
开发框架+
[英文] Understanding Modern Development Frameworks: A Guide for Developers and Technical Decision-makers
https://www.freecodecamp.org/news/understanding-modern-development-frameworks-guide-for-devs/
LangChain+
https://python.langchain.com/docs/tutorials/
New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications.
https://www.freecodecamp.org/news/beginners-guide-to-langchain/
LangChain is a popular framework for creating LLM-powered apps.
AutoGen+
https://microsoft.github.io/autogen/0.2/docs/Getting-Started/
AutoGen is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks.
https://www.youtube.com/watch?v=JmjxwTEJSE8
Whether you know everything there to AI Agents or are a complete beginner, I believe there is something to learn here.
RAG+
https://www.youtube.com/watch?v=sVcwVQRHIc8
Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer.
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
GPT+
https://www.youtube.com/watch?v=kCc8FmEb1nY
We build a Generatively Pretrained Transformer (GPT), following the paper "Attention is All You Need" and OpenAI's GPT-2 / GPT-3.
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