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Kuaishou Technology · Hangzhou, Beijing

# AI Agent研发工程师（上下文工程方向）

Hangzhou, Beijing 

Listed on Kuaishou Technology’s official careers site. Listed as of October 19, 2026. Check that it is still open and apply there.
[Apply on Kuaishou Technology’s careers site →](https://zhaopin.kuaishou.cn/#/official/social/job-info/29753)

[OpenNash Jobs](https://jobs.opennash.com/) / [Kuaishou Technology](https://jobs.opennash.com/companies/kuaishou-technology/) / AI Agent研发工程师（上下文工程方向）

## Job description
- 负责 RAG（检索增强生成）核心能力的研发与优化，包括检索策略、召回排序、知识融合等关键环节，持续提升生成质量和准确性；
- 设计和实现 Agent 长记忆机制，支持跨会话的信息持久化、记忆检索与更新，提升 Agent 的长期交互体验；
- 深入研究上下文工程底层技术，探索向量检索、混合检索、语义分块、查询改写等方向的效果优化；
- 关注 Agent 系统的整体技术演进，理解工具调用、规划执行、多智能体协作等核心机制，从上下文工程视角为 Agent 能力提升提供支撑；
- 跟踪上下文工程及 Agent 领域最新研究进展，快速验证和落地前沿技术方案；
- 建立效果评估体系，通过实验和数据驱动的方式持续迭代优化 RAG 和记忆系统的表现。
- 本科及以上学历，计算机、人工智能相关专业优先；
- 熟悉至少一种编程语言（如 Python、Golang、Java 等），掌握常用数据结构与算法，具备良好的编程基础；
- 对 RAG 技术有深入理解，熟悉主流 Embedding 模型、向量数据库（如 Milvus、Pinecone、Weaviate 等）及检索方案；
- 了解 LLM 技术原理及 Agent 系统核心机制，对上下文管理、工具调用、记忆机制等有一定认知；
- 有 NLP/IR 领域背景者优先，熟悉文本检索、语义匹配、信息抽取等技术；
- 积极主动，注重效果导向，能够独立设计实验方案并推动优化落地；
- 有顶会论文发表、RAG 相关开源项目贡献、或记忆系统实践经验者加分。

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Oct 19, 2026
- Last checked: Oct 19, 2026
- Listed for: Under a day
- Location: Hangzhou, Beijing[Apply on Kuaishou Technology’s careers site →](https://zhaopin.kuaishou.cn/#/official/social/job-info/29753)

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