岗位职责
- 深度参与小红书社区核心业务的研发攻坚，深入理解产品战略，主导从系统架构设计、核心代码编写到最终上线的完整生命周期；
- 拥抱AI-Native研发范式，借助AI 能力跨越技术边界，独立承担跨越前端、客户端与服务端的全栈开发，跨技术领域发展；
- 跟踪业内前沿的 AI 技术演进（如 LLM 应用、Agent 架构等），结合真实的社区互动场景，推动智能化创新功能的探索与工程化落地；
- 与产品、设计等上下游角色紧密协同，主动从工程视角发现体验痛点，驱动系统演进与架构升级。 【Job Responsibilities】
- Drive the development of core community systems: Deeply engage in the engineering development of rednote's core community products. Develop a thorough understanding of product strategy and take ownership of the entire development lifecycle, from system architecture design and core code implementation to production deployment.
- Embrace AI-native engineering and full-stack development: Leverage AI capabilities to expand beyond traditional technical boundaries. Independently take ownership of full-stack development across frontend, client-side, and backend systems, while continuously broadening your technical expertise.
- Explore and implement cutting-edge AI technologies: Stay up to date with emerging AI technologies, including LLM-powered applications and agent architectures. Apply them to real-world community interaction scenarios and drive the exploration, development, and production deployment of innovative AI-powered features.
- Drive product experience and technical evolution: Collaborate closely with product managers, designers, and other cross-functional partners. Proactively identify user experience pain points from an engineering perspective and drive system evolution and architectural improvements.
职位要求
- 本科及以上学历，计算机、软件工程、人工智能等相关专业优先；
- 具备深厚的计算机科学底蕴，熟悉数据结构、算法、网络与操作系统原理。精通至少一门主流开发语言（如 C/C++/Java/Go/Python 等），具备优秀的编码规范与工程素养；
- 拥有极强的技术好奇心与快速学习能力。在日常实践中，有重度使用生成式 AI 工具辅助开发与解决复杂问题的经验，能够快速掌握未知领域的技术；
- 具备极强的责任感与自驱力，逻辑思维缜密。能够穿透业务表象直击本质，以结果为导向，在复杂协作环境中高效推动项目落地。
- Educational background: Bachelor's degree or above in Computer Science, Software Engineering, Artificial Intelligence, or a related field is preferred.
- Strong computer science fundamentals: Solid understanding of data structures, algorithms, computer networks, and operating systems. Proficiency in at least one mainstream programming language, such as C/C++, Java, Go, or Python, with strong coding standards and engineering practices.
- Technical curiosity and rapid learning: Strong enthusiasm for technology and the ability to quickly master unfamiliar domains. Hands-on experience with intensive use of generative AI tools to support software development and solve complex engineering problems.
- Strong ownership and execution: A high level of responsibility, a self-driven mindset, and rigorous logical thinking. The ability to look beyond surface-level business requirements to identify underlying problems, stay focused on outcomes, and drive projects to successful delivery in complex, collaborative environments.
