Tech Lead – Digital Labs

1. Technical Leadership:

• Lead the architecture, design, and development of scalable, highly available, and fault-tolerant backend and frontend solutions.
• Provide expertise in microservices, RESTful API design, and modern frontend architectures (e.g., SPA, PWA).
• Guide teams in identifying trade-offs in technical debt and ensuring the creation of reusable components for long-term system maintainability.
• Collaborate with product, data science, and machine learning engineering teams to integrate intelligent, data-driven features into digital platforms.

1. Team Development:

• Mentor engineers across backend and frontend domains, fostering a collaborative and high-performing development culture.
• Actively support team growth through peer reviews, technical training, and enforcement of best practices in both backend and frontend development.

1. Collaboration Across Functions:

• Work closely with product management, data engineering, data science, and machine learning engineering teams to align technical solutions with business goals and ensure seamless data and ML model integration.
• Partner with IT infrastructure teams to implement CI/CD pipelines, infrastructure as code, and advanced monitoring strategies for frontend and backend systems.

1. Agile Development & Rapid Delivery:

• Drive agile development practices within the team, ensuring efficient sprints, iterative improvements, and timely delivery.
• Promote cloud-native backend and frontend development using DevOps practices, automation, and performance monitoring tools.

1. Continuous Improvement:

• Evaluate emerging backend, frontend, and data/ML technologies to drive innovation and improve system performance, maintainability, and cost-effectiveness.
• Ensure adherence to engineering best practices, such as linting, unit testing, end-to-end testing, and security scanning.

1. Educational Background:

• Bachelor’s degree in Computer Science, Software Engineering, or a related field. Advanced degrees are a plus.

1. Technical Expertise:

• Architecture and Design:
• Proven ability to design and deploy high-performance backend and frontend solutions, incorporating security, fault tolerance, and scalability.
• Advanced knowledge of microservices, backend-for-frontend patterns, and modern frontend architectural styles (SPA, PWA).
• Backend:
• Proficiency in programming languages like Java, Python, Go, or Node.js, with expertise in frameworks such as Spring, Django, Flask, or Express.
• Strong database modeling skills and experience with both relational (PostgreSQL, MySQL) and non-relational (MongoDB, Redis) databases.
• Frontend:
• Proficiency in JavaScript and TypeScript, along with frameworks like React, Vue.js, or Angular, and their ecosystems (e.g., Ant Design, Axios).
• Expertise in bundling tools (e.g., Webpack, Vite) and frontend hosting and deployment tools, such as Nginx, Docker, CDN, and cloud deployment strategies.
• Sufficient understanding of UX principles to contribute to user experience optimization.
• Cloud-Native Development:
• Proven experience building and deploying cloud-native solutions on AWS, Azure, or Google Cloud, with familiarity in serverless computing and container orchestration (Docker, Kubernetes).
• Proficiency in infrastructure-as-code tools (e.g., Terraform, Ansible) and monitoring solutions (e.g., Prometheus, Grafana).
• Data and Machine Learning Integration:
• Familiarity with integrating data pipelines and machine learning models into digital platforms, ensuring seamless deployment and performance.
• Understanding of RESTful APIs for data science and ML services, and experience with frameworks like TensorFlow Serving, MLflow, or similar tools.
• Engineering Best Practices:
• Deep understanding of agile engineering practices, including RESTful API design, unit/E2E testing, and DevOps tools such as CI/CD pipelines.

1. Experience:

• 8+ years of software development experience with 2+ years in a technical leadership role.
• Proven track record of delivering at least two large-scale products or projects involving significant backend and frontend components.

1. Soft Skills:

• Strong problem-solving and analytical skills to lead technical decision-making across backend and frontend domains.
• Excellent communication skills to collaborate effectively with cross-functional teams.
• Demonstrates a strong sense of ownership, adaptability, and self-motivation.
• Experience driving agile practices within a diverse development team.

1. Preferred:

• Background AI or digital transformation is a strong plus.
• Proficiency in Mandarin and English.

中文版本

岗位说明

本职位隶属于全球数智科技部的Digital Labs。Digital Labs是一支由软件工程、数据工程、数据科学、机器学习工程、生物信息学和产品管理等领域的热情人才组成的数字产品团队。我们专注于打造业内领先的数字产品和平台，加速生物药物研究、工艺开发与制造的速度和质量，为改善人类健康做出贡献。

该岗位负责开发团队的技术领导工作，与产品管理、数据和技术基础设施团队密切协作，确保项目的技术卓越性。技术负责人将引导团队定义产品技术架构，实施敏捷开发实践，并实现快速且高质量的交付。在可扩展性、云原生和用户体验为中心的系统中，具备高级产品架构和软件工程专业知识是领导创新解决方案的关键。

主要职责

1. 技术领导:

• 负责可扩展、高可用、容错的后端和前端解决方案的架构设计和开发工作。
• 提供微服务架构、RESTful API设计以及现代前端架构（如SPA、PWA）的专业知识。
• 引导团队权衡技术债务，确保创建可重用组件以实现系统的长期可维护性。
• 与产品、数据科学和机器学习工程团队合作，将智能数据驱动功能集成到数字平台中。

1. 团队发展:

• 指导后端和前端领域的工程师，营造协作和高绩效的开发文化。
• 通过代码审查、技术培训及在后端和前端开发的最佳实践中提供支持，推动团队成长。

1. 跨职能协作:

• 与产品管理、数据工程、数据科学和机器学习工程团队密切合作，确保技术解决方案与业务目标一致，并实现数据与机器学习模型的无缝集成。
• 与IT基础设施团队合作，实施CI/CD、基础设施即代码以及前后端系统的监控策略。

1. 敏捷开发与快速交付:

• 在团队内推动敏捷开发，确保高效迭代和按时交付。
• 推广使用DevOps、自动化和性能监控工具的云原生后端和前端开发。

1. 持续改进:

• 评估新兴的后端、前端以及数据/机器学习技术，以推动创新并改善系统性能、可维护性和成本效益。
• 确保遵循开发最佳实践，例如代码规范、单元测试、端到端测试和安全扫描。

任职要求

1. 教育背景:

• 计算机科学、软件工程或相关领域的本科及以上学历，硕士优先。

1. 技术专长:

• 架构与设计:
• 具备设计和部署高性能后端和前端解决方案的能力，包括安全性、容错性和可扩展性。
• 熟悉微服务、后端适配前端模式及现代前端架构风格（SPA、PWA）。
• 后端:
• 精通Java、Python、Go或Node.js等编程语言，以及Spring、Django、Flask或Express等框架。
• 拥有强大的数据库建模技能，熟悉关系型数据库（PostgreSQL、MySQL）和非关系型数据库（MongoDB、Redis）。
• 前端:
• 精通JavaScript和TypeScript，以及React、Vue.js或Angular等框架及其生态系统（如Ant Design、Axios）。
• 掌握打包工具（如Webpack、Vite）以及前端托管和部署工具（如Nginx、Docker、CDN和云部署策略）。
• 具备足够的用户体验（UX）知识，为优化用户体验提供建议。
• 云原生开发:
• 拥有在AWS、Azure或Google Cloud上构建和部署云原生解决方案的实践经验，熟悉无服务器计算和容器编排（Docker、Kubernetes）。
• 熟练掌握基础设施即代码工具（如Terraform、Ansible）及监控解决方案（如Prometheus、Grafana）。
• 数据与机器学习集成:
• 熟悉将数据管道和机器学习模型集成到数字平台的方法，确保无缝部署与高效性能。
• 理解数据科学和机器学习服务的RESTful API设计，熟悉TensorFlow Serving、MLflow或类似工具。
• 工程最佳实践:
• 深刻理解敏捷工程实践，包括RESTful API设计、单元测试/端到端测试以及CI/CD等DevOps工具。

1. 工作经验:

• 8年以上软件开发经验，其中至少2年以上技术团队领导经验。
• 具备至少两个涉及重大后端和前端组件的大型产品或项目的交付记录。

1. 软技能:

• 具备较强的问题解决和分析能力，能够在后端和前端领域内进行技术决策。
• 出色的沟通能力，能够高效地跨团队合作。
• 表现出强烈的责任感、适应能力和自我驱动力。
• 在多样化的开发团队中推动敏捷开发的经验。

1. 优先条件:

• 拥有人工智能或数字化解决方案背景优先。
• 熟练使用中英文工作者优先