IT Solution Architecture

该职位来源于猎聘 A brief summary of the provided position as below 本职位概述如下：

Responsible for digital transformation and smart manufacturing architecture design, demand analysis, system integration, solution planning and delivery governance. Lead the design of IT/OT converged architecture, ensure system feasibility, scalability and security, support the construction of smart factory, data platform and business automation. 负责企业智能制造与数字化转型项目的架构设计、需求分析、方案规划与交付管控；设计 IT/OT 融合架构，主导 MES/WMS/ERP/PLM/SCADA 系统集成，支撑智慧工厂与数据平台建设。 Essential Duties and Job Responsibilities 主要职责 To perform this job successfully, an individual must be able to perform each essential duty satisfactorily: 胜任此项职位，需要有能力成功地履行如下主要工作职责:

Key Responsibilities / 岗位职责 Analyze business requirements in manufacturing scenarios: production, quality, equipment, warehouse, planning and supply chain. 梳理制造场景业务需求：生产、质量、设备、仓储、计划、供应链。 Design enterprise IT/OT architecture, application architecture, data architecture and integration architecture. 设计企业 IT/OT 架构、应用架构、数据架构与集成架构。 Lead solution design, technical selection and vendor evaluation for smart manufacturing systems. 负责智能制造系统方案设计、技术选型与厂商评估。

Design system interfaces, data flow, deployment scheme and architecture standards. 设计系统接口、数据流、部署方案与架构规范。 Prepare solution proposals, technical documents, bidding documents and architecture diagrams. 编写解决方案、技术文档、招标材料与架构图纸。 Support project implementation, technical review, risk control and problem solving. 支持项目落地、技术评审、风险管控与问题攻关。 Promote the application of IIoT, cloud, big data and digital technologies in manufacturing. 推动工业物联网、云、大数据与数字化技术在工厂落地。 Deeply engage with production, process, equipment, quality and manufacturing supply chain scenarios, identify business pain points, conduct requirement breakdown, feasibility study and ROI analysis, and deliver manufacturing AI scenario roadmap. Lead cross-team alignment to unify solution scope and delivery schedule. 深入车间生产、工艺、设备、质量、供应链制造环节，梳理业务痛点与数字化需求，完成需求拆解、可行性评估、投入产出分析，输出制造域AI场景蓝图与落地路线图；主导跨团队对齐，统一方案口径与落地节奏。 Design end-to-end AI solutions for typical manufacturing scenarios including visual quality inspection, equipment predictive maintenance, process parameter optimization, yield improvement, energy optimization, production forecasting and intelligent scheduling. Cover scenario definition, data pipeline, model design, deployment strategy and system integration, balancing business value, technical feasibility, system stability and O&M cost. 针对工业视觉质检、设备故障预警、工艺参数优化、良率提升、能耗优化、生产预测、智能排产等场景，设计完整AI解决方案，包含场景方案、数据方案、模型方案、部署方案与集成方案；兼顾业务价值、技术可行性、系统稳定性与运维成本。 Design AI data ingestion, cleansing, feature engineering, sample management and data feedback loop based on existing MES, SCADA, PLC, IoT and enterprise data platforms. Ensure AI data compliance, traceability and reusability in line with corporate data governance rules, and resolve cross-domain data collaboration issues. 基于企业现有MES、SCADA、PLC、IoT、数仓与数据平台架构，设计AI数据接入、清洗、特征工程、样本管理与数据回流链路；遵循公司数据治理规范，保障AI数据合规、可追溯、可复用，解决跨域数据协同问题。 Lead architecture governance throughout AI project lifecycle, coordinate algorithm, data, development, delivery and infrastructure teams, control solution quality, iteration and acceptance. Standardize manufacturing AI solution templates and architecture guidelines to improve delivery reusability. 牵头AI项目实施全过程架构管控，协调算法、数据、开发、交付、基础设施团队，把控方案落地质量、迭代优化与上线验收；沉淀制造域AI方案模板、架构规范与落地标准，提升团队交付复用能力。 Research industrial AI, LLM, AI Agent, digital twin, computer vision and time-series prediction technologies, conduct technical selection and PoC verification for manufacturing scenarios, and continuously upgrade domain AI technical capability. Manage cross-team collaboration and ensure solutions meet business goals and architecture standards. 跟踪工业AI、大模型、AI Agent、数字孪生、机器视觉、时序预测等前沿技术，结合制造业务特性进行技术选型与场景验证，输出技术预研报告，持续迭代制造域AI技术体系。 Requirements / 任职要求 Bachelor’s degree or above in Computer, Automation, Mechanical, Electronic or related major. 本科及以上学历，计算机、自动化、机械、电子等相关专业。 3–6 years of experience in IT architecture or solution design in manufacturing industry. 3–6 年制造业 IT 架构或解决方案设计经验。 Familiar with manufacturing systems: MES/MOM, WMS, ERP, APS, PLM, SCADA, IIoT. 熟悉制造类系统：MES/MOM、WMS、ERP、APS、PLM、SCADA、IIoT。 Ability to design end-to-end solutions and system integration architecture independently. 能够独立设计端到端解决方案与系统集成架构。 Familiar with factory production workflow, process management, equipment maintenance and quality management system. Deep understanding of typical smart manufacturing AI use cases, capable of delivering full lifecycle solution independently. 熟悉工厂生产流程、工艺管理、设备运维、质量管控体系，深刻理解智能制造典型AI落地场景，能够独立完成从需求调研、方案设计到落地交付的全流程工作。 Good command of technical documentation, architecture diagramming and solution presentation. 具备良好的技术文档、架构制图与方案呈现能力。 Strong communication, coordination and problem-solving ability in a manufacturing plant environment. 具备良好的沟通协调与工厂现场问题解决能力。 Client-side experience in manufacturing enterprise is highly preferred. 有制造企业甲方工作经验优先。 Preferred Qualifications

优先条件 Experience in smart factory, digital workshop or IT/OT integration projects. 具备智慧工厂、数字车间或 IT/OT 融合项目经验。 Knowledge of industrial network, data collection, edge computing or digital twin. 了解工业网络、数据采集、边缘计算、数字孪生。 Experience in project management, bidding, vendor management or architecture governance. 具备项目管理、招投标、厂商管理或架构治理经验。 Relevant certifications: PMP, ITIL, cloud or architecture certification. 持有 PMP、ITIL、云认证或架构类认证优先。