Job Title: Senior Software Engineer (Backend) - Data and AI
Report to: Software Development Team Manager
Direct reports: N/A
职位：高级软件工程师(后端) - 数据与AI方向
汇报对象：软件研发团队经理
下属：无
Mission
As a key player in software development team, your mission is , on the basis of Atlas Copco standards practices, to continuously optimize and innovate, particularly in realm of data and AI, also within team discussions and contribute to necessary product functions, work content and work plan, design, write, test and debug software product modules or overall technical framework, solution details, functional modules, etc., develop specific communication protocols, API, SDK, component, interfaces, Middle-layer, underlying frameworks, class libraries, etc., output stable, high-performance, high-availability back-end service programs with data capability or AI Inside, Targeting to achieve the purpose of delivering stable and reliable overall product solutions. Develop software capabilities with other members of the R&D team to optimize the quality of software system and products.
Additionally, you will be responsible for integrating big data Technology and AI technologies into our backend systems and scalable data storage solutions, including designing and implementing data processing pipelines, machine learning or deep learning models or other necessary AI tech mode ,eg. AI Agentic Framework. Your role will also involve collaborating with data experts and other stakeholders to drive innovation in data-driven applications and intelligent systems.
Workingclosely with the software team and related stakeholder, including architect, developer, tester, PO, scrum master, quality, incident specialist, etc., you will play a pivotal role in driving technological innovation and excellence. Your responsibilities extend beyond mere developing and execution; you will also inspire and mentor team members in some necessary working activity, fostering a R&D engineering culture of continuous learning and improvement. By championing robust and scale-able technology solutions, you will contribute to the creation of top-level software products and system that meet and exceed industry standards, you are reporting to Our software R&D manager at our Innovation Center Asia.
作为软件研发团队的关键成员，您的使命是在阿特拉斯·科普柯（Atlas Copco）标准实践的基础上，持续优化和创新，特别是在数据和人工智能领域。您需要在团队讨论中积极参与，为必要的产品功能、工作内容和工作计划做出贡献。您将负责设计、编写、测试和调试软件产品模块或整体技术框架、解决方案细节、功能模块等，开发特定的通信协议、API、SDK、组件、接口、中间层、底层框架、类库等，输出具备数据能力或内置人工智能的稳定、高性能、高可用性的后端服务程序，目标是提供稳定可靠的完整产品解决方案。您还将与其他研发团队成员合作，提升软件系统和产品的质量。
同时，您将重点负责将大数据技术以及人工智能技术整合到我们的后端系统和可扩展的数据存储解决方案中，包括设计和实施数据处理管道、机器学习或深度学习模型或其他必要的 AI 技术模式，例如 AI 代理框架。您的职责还将涉及与数据专家和其他利益相关者合作，推动数据驱动应用和智能系统中的创新。
通过与我们软件研发团队成员以及利益相关方密切合作，您将在推动技术创新方面发挥关键作用。您的责任不仅仅局限于开发和执行；在必要的工作活动中，您也将激励和指导团队成员，培养持续学习和改进的研发工程文化。通过倡导强大且可扩展的技术解决方案，你将在打造符合并超越行业标准软件产品和系统上做出贡献，您将向我们亚洲创新中心的软件产品研发团队经理汇报。
Major Responsibilities
Duties and responsibilities include, but are not limited to:
61 Participate in or be responsible for the formulation of software technical solutions and architectural design, especially in realm of data and AI.
61 Focus on integrating big data and AI technologies into backend systems, including data processing pipelines and machine learning models.
61 Develop core software products, including but not limited to monitoring platforms, data analysis platforms, and industrial software systems.
61 Write high-quality, efficient, readable, and maintainable C#/Golang/Python code, including unit tests, necessary automation testing .
61 Develop business functions, data models, technical architectures, and basic protocols required within the scope of Atlas Copco's assembly and tightening.
61 Design and implement scalable data storage solutions, such as data lakes and data warehouse solutions.
61 Be responsible for code quality and stability, including code reviews, performance optimization, and necessary technical decisions.
61 Use big data frameworks to process large datasets, and continuously optimize real-time and batch processing data pipelines. e.g. Kafka, Spark, Flink, Fluss.
61 Collaborate with necessary data science experts to integrate machine learning or deep learning models and AI frameworks such as Agentic Framework into software systems.
61 Use AI frameworks (such as TensorFlow, PyTorch) for model training, optimization, deployment, and monitoring, if necessary.
61 Collaborate with other technical teams or engineers to ensure that the applications or modules you develop are integrated with Atlas Copco's existing systems and meet the requirements and delivery targets of the software product definition.
61 Author and review technical proposals, detailed designs, and functional specifications, including technical specifications and necessary user guides, and be able to share them in a timely manner with the team or stakeholders.
61 Create standardized solutions for common cases to drive high-quality delivery and conduct necessary tech cost and time estimates.
61 Design and implement efficient, robust, and scalable backend microservices or containerized microservices and APIs.
61 Ensure the logging and storage of system and module boundary logs to ensure the traceability of system issues and problems.
61 Collaborate with cross-functional teams to ensure that software design is aligned with business objectives and product requirements.
61 Participate in key stages of product and technology innovation, and supervise software testing and debugging on-site at suppliers or in the workshop, as required.
61 Ensure the security, compliance of data processing and storage solutions, as well as the interpretability and fairness of AI models.
61 Participate in and promote team collaboration as well as the construction of TIIP + Diversity & Inclusive within team.
61 Collaborate with global software development teams and be able to share global experience with Chinese teams and vice versa.
61 Keep track of new technology trends in a timely manner and share them with the team, such as AI, big data, and industrial robotics.
61 Travel domestically and internationally as required.
任务职责包括但不限于:
61 参与或者负责软件技术方案的制定以及架构设计，尤其数据与AI领域。
61 专注于将大数据和AI技术整合到后端系统中，包括数据处理管道和机器学习模型。
61 开发公司核心软件产品，包括但不限于监控平台、数据分析平台工业软件系统等。
61 编写高质量、高效、易读和可维护的 C#/Golang/Python 代码,包括单元测试。
61 开发Atlas Copco装配拧紧范围内所需的业务功能、数据模型、技术架构与基础协议。
61 设计并实现可扩展的数据存储解决方案，如数据湖，数据仓方案。
61 负责相关代码质量和稳定性，包括代码审查、性能优化以及必要的技术决策。
61 使用大数据框架（如Kafka、Spark、Flinks、Fluss）处理大型数据集，并持续优化实时和批处理的数据pipeline。
61 与必要的数据科学专家合作，将机器学习或深度学习相关领域模型及Agentic Framework等AI框架集成到软件系统中。
61 如必须，使用AI框架（如TensorFlow、PyTorch）进行模型训练、优化、部署和监控。
61 与其他技术团队或者工程师合作，确保你开发应用程序或者模块与Atlas Copco现有的其他系统集成，并满足软件产品定义的需求与交付目标。
61 编写和审查、技术方案、详细涉及以及功能说明文档，包括技术规格甚至必要的用户指南，并能及时团队团队或者Stakeholder分享。
61 为常见设计创建标准方案以推动高质量交付，并进行必要的技术成本和时间评估。
61 设计并实现高效、健壮、可扩展的后端微服务或容器化的微服务和API。
61 确保系统和模块边界日志的记录和存储，以确保系统问题和问题的可追溯。
61 与跨职能团队合作，确保软件设计与业务目标、产品需求相一致。
61 涉及产品与技术创新的关键阶段，按需参与供应商现场或车间监督软件测试和调试。
61 确保数据处理和存储解决方案的安全性、合规性，以及AI模型的可解释性和公平性。
61 参与并推进团队协作以及团队的TIIP + Diversity & Inclusive建设。
61 与全球软件开发团队合作，并能够将全球经验分享给中国团队，反之亦然。
61 及时跟踪新技术趋势并与团队分享，如AI、大数据、工业机器人。
61 按需进行必要的国内和国外出差。
Education & Experience
61 Bachelor or Master of Science in software, computer or electronics, engineering or mathematical or similar major fields.
61 2+ years in using modern devops toolsets, writing dockerfile,yaml etc.
61 5+ years in developing C#/Python and 3+ years in developing Golang.
61 Experience in Object-oriented and combination-oriented design.
61 Experience in Software development under Microsoft Windows and Linux
61 Experience with distributed tracing and logging systems
61 Experience with performance monitoring and optimization
61 Experience with databases such as MySQL, PostgreSQL, and MongoDB .etc
61 Experience with Git,Gitlab, AzurePipeline,Jenkins, ArgoCD etc.
61 Good communication skills, able to work efficiently in a diversity environment.
61 Experience in co-working in an agile scrum team at R&D.
61 Experience in industrial manufacturing or related industry is preferred.
61 Experience with big data processing frameworks such as Apache Spark or Hadoop.
61 Familiarity with machine learning frameworks and libraries ,e.g., TensorFlow, PyTorch, Scikit-learn.
Knowledge & Skills
61 Proficiency in 2-3 Program languages among C#, Golang, Python, C/C++, and Java.
61 Proficient in using 2-3 common frameworks in C# and Go, such as Micro, Beego, Orleans, Flask, etc.
61 Proficient in using tools/systems like Git, GitLab, Azure Pipeline, Jenkins, and ArgoCD etc.
61 Proficient in using RESTful APIs, gRPC, and common protocols, and skilled in integrating software systems with other systems and services.
61 Deep understanding of microservices architecture and containerization technologies (such as Docker and Kubernetes).
61 Proficiency in the use and application optimization of relational and non-relational DBs (such as PostgreSQL, SQLite, MongoDB).
61 Proficient in the use and optimization of vector databases to support AI applications e.g. Pinecone, Milvus.
61 Proficient in AI frameworks (such as LangChain, AutoGen) and able to build and optimize agent-driven applications.
61 Ability to train, optimize, deploy, and monitor models based on deep learning or machine learning etc.
61 Mastery of big data processing frameworks (such as Flink, Spark, Fluss) and the practice of combining AI with big data.
61 Ability to monitor and optimize backend service and AI model performance, balancing model accuracy and speed.
61 Understanding of AI model interpretability and fairness, and the ability to ensure model transparency and compliance.
61 Strong problem analysis and resolution skills, with the ability to design and implement scalable and maintainable solutions.
61 Ability to use tools such as pprof, expvar, OpenTelemetry, NET Memory Profiler, dotTrace to monitor and optimize program and system performance.
61 Good communication skills, with the ability to work efficiently in a diverse environment.
61 Fluent communication skills in both Chinese and English
Personality & Behavior Traits
61 A high sense of responsibility and self-motivation
61 Creativity and an open-minded personality
61 Software quality and efficiency awareness
61 A sense of urgency and awareness of timelines and planning.
61 Innovative and curious on new technology with hands-on it.
61 User and business-oriented mindset
61 Transparent work with team
教育和经验要求：
61 软件、计算机或电子工程、工程学或数学等相关领域的学士学位及以上。
61 3年以上使用现代DevOps工具链的经验，如编写Dockerfile、YAML。
61 5年以上C# /Python开发经验且有3年以上开发Golang的经验。
61 在Microsoft Windows和Linux环境下软件开发的经验。
61 扎实的软件工程实践经验，包括单元测试、持续集成和持续部署。
61 具有AI以及分布式跟踪和日志系统的经验及性能监控和优化经验。
61 具有AI模型生命周期管理，包括模型训练、部署、监控和优化经验。
61 有使用AI框架（如LangChain、AutoGen、SK）进行智能系统开发的经验。
61 有使用大数据处理框架（如Spark,Flink,Fluss）的经验。
61 有机器学习框架和库（如TensorFlow、PyTorch、Scikit-learn）的使用经验。
61 了解AI模型的可解释性和公平性，能够确保模型的透明度和合规性。
61 有在研发敏捷scrum团队中协同工作的经验。
61 有工业大数据系统应用、工业制造或相关行业经验者优先。
知识技能：
61 精通C#、Golang、Python、C/C++、Java中2-3种编程语言。
61 在C#和Go中熟练使用2-3个常见的框架，如micro/beego/Orleans /Flask等。
61 熟练使用Git、Gitlab、Azure Pipeline，Jenkins、ArgoCD 等工具/系统。
61 熟练使用RESTful API,gRPC以及通用协议，熟练软件系统与其他系统和服务的集成。
61 对微服务架构和容器化技术（如Docker和Kubernetes）有一定的深入理解。
61 精通关系和非关系型DB（如Postgre、Sqlite、MongoDB的使用和应用优化。
61 熟练向量数据库（如Pinecone、Milvus）的使用和优化，以支持AI应用。
61 熟练使用AI框架（如LangChain、AutoGen），能够构建和优化智能体驱动的应用。
61 能够基于深度学习或者机器学习的模型进行训练、优化、部署和监控。
61 掌握大数据处理框架（如Flink、Spark、Fluss）以及AI与大数据结合的实践。
61 具备AI模型性能监控和优化的能力，能够平衡模型的准确性与速度。
61 了解AI模型的可解释性和公平性，能够确保模型的透明度和合规性。
61 具有强力的问题分析与解决能力，能够设计和实现可扩展、易于维护的解决方案。
61 能够使用pprof, expvar,OpenTelemetry,NET Memory Profiler,dotTrace等工具监控和优化程序和系统性能。
61 良好的沟通能力，能够在多元化环境中高效工作。
61 流利的中英文沟通表达能力。
性格和行为特质：
61 高度的责任感和自我驱动力。
61 有创造力以及保持***的性格。
61 软件质量和效率意识。
61 有紧迫感和时间点与计划意识
61 对新技术有创新精神和好奇心，并能亲身实践。
61 以用户和业务为导向的思想。
61 与团队一起保持工作透明。