2027届-种子计划C-数字化（AI Engineer）-全球数智科技部

We are the Global Digital Technology department at WuXi Biologics. We are committed to leveraging cutting-edge computer technologies to reshape the R&D, manufacturing, and commercialization processes in biopharma. From intelligent parsing of vast amounts of scientific literature to automated orchestration of laboratory workflows and semantic search of internal knowledge bases—here, you will see how Large Language Models and AI Agents take root in life-saving scientific scenarios. We are looking for a backend/AI development intern with solid engineering skills to join our AI Application Team. You won’t just be running demos in Jupyter Notebooks; you will need to build stable, scalable backend services and deploy complex agent reasoning logic as APIs or internal tools for our scientists and engineers. This role sits at the intersection of Software Engineering and Applied AI Research. Responsibilities:

1. 01

   Agent Application Development: Design and develop specialized agents for biopharma scenarios (e.g., automated experimental report generation, internal SOP Q&A bots) based on LangGraph, DeepAgent, or other agent frameworks.

2. 02

   Backend Services & API Design: Develop agents using Python (FastAPI/Flask) and encapsulate them into stable backend services, while designing clear data interfaces and error handling mechanisms.

3. 03

   RAG System Optimization: Implement high-performance document parsing, vector retrieval, and reranking logic for unstructured biopharma data (PDF papers, internal documents, experimental records).

4. 04

   Engineering Efficiency: Write clean, maintainable, modular code; participate in code review and CI/CD processes; write technical documentation.

1. 01

   Education: Current undergraduate/master’s/PhD student in Computer Science (CS), Electrical Engineering (EE), Software Engineering, or a related STEM field.

2. 02

   Hardcore Coding Skills: - Proficient in Python with good object-oriented programming practices. - Solid understanding of data structures and algorithms, and basic knowledge of concurrent programming and asynchronous I/O (AsyncIO). - Familiar with Git version control and Linux command-line operations.

3. 03

   Backend Intuition: Understand how to design RESTful APIs, and know about environment variables, database connection pools, and Docker containerization.

4. 04

   AI Theoretical Knowledge: Deep understanding of agent architecture, harness engineering, function calling principles; knowledge of basic RAG workflows and other AI techniques.

5. 05

   Agent Hands-On Experience Preferred: Have a GitHub project demonstrating use of LangChain/LangGraph to build multi-agent systems, or have participated in AI hackathons.

6. 06

   Familiarity with Biopharma Terminology Preferred: You don’t need a pharmacy degree, but if you know what ADCs, clinical trial phases, or PubMed are, we’ll be very interested. Important Note: If you have a GitHub / tech blog / past project demo links, please be sure to include them. We value the quality of your Pull Requests far more than your GPA. 岗位说明: 我们是药明生物的 Global Digital Technology 部门。我们致力于利用前沿的计算机技术重塑生物制药的研发、生产与商业化流程。从海量科研文献的智能解析，到实验室流程的自动化编排，再到内部知识库的语义检索——在这里，你将看到 Large Language Model 与 AI Agent 如何在拯救生命的科学场景中落地生根。 我们正在寻找一名工程能力扎实的后端/AI开发实习生，加入我们的AI应用小组。你将不仅仅是在 Jupyter Notebook 里跑 Demo，而是需要构建稳定、可扩展的后端服务，并将复杂的 Agent 推理逻辑部署为可供内部科学家和工程师调用的 API 或内部工具。这是一个介于 Software Engineering 与 Applied AI Research 之间的角色。 岗位职责:

7. 01

   智能体应用开发 ：基于 LangGraph、DeepAgent 或者其他智能体框架，设计并开发面向生物制药场景的专用 Agent（如：实验报告自动生成、内部 SOP 问答机器人）。

8. 02

   后端服务与 API 设计 ：使用 Python (FastAPI/Flask) 开发Agent，并封装为稳定的后端服务，同时设计清晰的数据接口和错误处理机制。

9. 03

   RAG 系统优化 ：针对生物医药领域的非结构化数据（PDF 论文、内部文档、实验记录），实现高性能的文档解析、向量检索与重排序逻辑。

10. 04

    工程效能提升 ：编写干净、可维护、模块化的代码；参与 Code Review 与 CI/CD 流程；编写技术文档。 岗位要求:

11. 01

    学历：计算机科学 (CS)、电子工程 (EE)、软件工程或相关 STEM 专业的在读本科/硕士/博士。

12. 02

    硬核代码能力： - 熟练掌握 Python，具备良好的面向对象编程习惯。 - 扎实的数据结构与算法基础，能够理解并发编程和异步 IO（AsyncIO）的基本原理。 - 熟悉 Git 版本控制与 Linux 命令行操作。

13. 03

    后端直觉 ：了解如何设计 RESTful API，明白什么是环境变量、数据库连接池和 Docker 容器化。

14. 04

    AI理论素养 ：深入理解 Agent 架构、Harness Engineering、Function Calling 的原理；了解 RAG 等AI技术的基本流程。

15. 05

    有 Agent 实战经验更佳 ：有 Github 项目展示使用过 LangChain/LangGraph 构建 Multi-Agent 系统，或参加过各类 AI Hackathon。

16. 06

    熟悉生物医药术语更佳 ：不需要你是药学院出身，但如果你知道什么是 ADC、Clinical Trial Phases 或者 PubMed，我们将非常感兴趣。 重要提示：如果你有 GitHub / 技术博客 / 过往项目的 Demo 链接，请务必附上。我们更看重你提交的 Pull Request 质量，而非 GPA