岗位概述
参与 AI Agent 中台的架构设计与核心功能开发，构建生产级 Agentic AI 系统，将前沿 AI 工具理论转化为解决多业务领域问题的真实应用。
本岗位为 2026 年暑期实习，全职实习时长 5 个月以上。实习期间表现优秀者，将有机会获得留用。
职责描述
- 设计、实现并部署 AI 智能体，构建具备长短时记忆管理、复杂工作流状态机编排以及外部知识库检索能力的服务架构
- 参与 AI Agent 中台的架构设计与核心功能开发（含系统前后端接口研发）
- 构建 Agent 自动化评测框架，对不同大模型的 Agent 能力进行深度评估
- 推进平台的性能监控与全链路可观测性建设
- 跟进业界最新 Agent 论文和框架，参与内部技术预研
任职资格
- 本科及以上学历在读，计算机、软件工程、人工智能等相关专业优先（2027 届及以后）
- 熟练掌握 Python / JavaScript / TypeScript / Java / Go / C++ 等至少一种主流语言，具备扎实的算法与数据结构基础
- 具备 Agent 系统开发经验，掌握 LangGraph / ADK / AgentScope 等框架及实现原理；了解 Claude Code 等前沿 Agent 实现机制，能设计高可用、高扩展性的大模型工程架构
- 掌握 Prompt 工程、RAG、Tool Calling、Harness Engineering、Skills 等 AI 应用关键技术
- 具备良好的沟通表达能力，能清晰阐述架构权衡与技术决策；学习能力强，有独立解决问题的能力
加分项
- 在 GitHub 等开源社区的 Agent 相关生态中有实际 PR 贡献
- 了解机器学习/深度学习框架，有 Transformer 等模型实战经验
▸ Overview
You'll join the team building production-grade Agentic AI systems — turning cutting-edge research into real applications that solve complex business problems across the company.
This is a full-time summer 2026 internship (5+ months). Strong performers will be considered for a return offer.
▸ Responsibilities
- Design, implement, and deploy AI agents with long/short-term memory management, complex workflow orchestration, and external knowledge retrieval
- Contribute to AI Agent platform architecture design and core feature development, including frontend/backend interfaces
- Build automated evaluation frameworks to benchmark agent capabilities across different LLMs
- Drive platform performance monitoring and end-to-end observability
- Track the latest agent research and frameworks; participate in internal technical exploration
▸ Qualifications
- Bachelor's degree or above, currently enrolled (graduating 2027 or later), preferably in CS, Software Engineering, or AI
- Proficiency in at least one mainstream language (Python, JavaScript/TypeScript, Java, Go, C++, etc.); strong algorithms and data structures fundamentals
- Hands-on Agent development experience with LangGraph, ADK, AgentScope, or similar frameworks; familiarity with frontier agents like Claude Code; ability to design scalable LLM engineering architectures
- Solid grasp of Prompt Engineering, RAG, Tool Calling, Harness Engineering, and Skills
- Clear communicator who can articulate architectural trade-offs; strong independent problem-solving ability
▸ Bonus Points
- Actual PR contributions to Agent-related open-source projects on GitHub or similar platforms
- Experience with ML/DL frameworks; hands-on work with Transformer-based models