architect岗位职责

Qualification:·Good analytical skills to understand complex requirements and how tofind the “right” IT solution·Definition of scalable architecture, IT system interfaces integration·Documentation of IT system infrastructure·Know-how in Web service, cabled IT system, IBM DataPower·Know-how about Service Monitoring and System Monitoring, know-how inmonitoring tools e.g. HP BSM·Definition of security assessment·Sophisticated solutions and module-based setup

【岗位职责】
1.云基础架构设计（Landing Zone）：负责基于阿里云的大客户架构设计，包括但不限于资源规划、账号体系设计、网络拓扑（VPC）、安全合规基线、身份权限管理（RAM）及成本财务管理，确保云环境的安全、可扩展与合规。
2.AI平台架构设计：在稳固的云基础之上，设计面向AI/机器学习工作负载的技术架构。包括数据存储方案、AI算力（GPU/NPU）调度、模型训练/推理环境、MLOps（机器学习运维）流程设计以及AI服务与业务系统的集成方案。
3.客户需求分析与方案输出：深入理解客户的业务场景和痛点，将业务需求转化为高可用的技术解决方案。独立撰写高质量的招投标技术标书、技术方案及汇报PPT。
4.技术布道与沟通：作为技术发言人，向客户CXO级或技术团队清晰讲解架构设计思路、技术选型优势及落地路径，消除客户技术顾虑，建立信任。
5.项目实施与落地：具备动手能力，能够领导或核心参与POC（概念验证）环境搭建，指导开发/运维团队进行落地实施，解决实际部署中遇到的技术难题，确保架构设计的*终交付质量。
【任职要求】
1.工作经验：本科及以上学历，计算机相关专业，5年以上云架构或系统设计经验，其中至少2年以上AI/大数据相关项目的架构设计经验。
2.云平台专家：深度熟悉阿里云产品体系，精通其中至少一项核心领域（如网络、计算、安全、大数据）。熟悉云Landing Zone方法论，有实际的大规模上云规划与治理经验。持有阿里云ACE/ACP认证者优先。
3.AI技术栈理解：对AI技术栈有清晰认知，了解主流深度学习框架（TensorFlow, PyTorch），熟悉AI训练/推理的算力需求，了解AI开发平台（如阿里云PAI）或MLOps理念。
4.架构能力：具备优秀的抽象思维和架构设计能力，熟悉TOGAF等架构框架，能够在高可用、容灾、安全性和成本之间做出合理权衡。
5.沟通与方案能力：具备流利的英语听说读写能力（需可作为工作语言，直接与客户或海外团队沟通）。拥有出色的文档撰写能力和PPT讲解能力，临场反应快，能够应对客户的技术挑战。
6.落地能力：熟悉Linux、容器（Docker/K8s）、Infrastructure as Code（Terraform）等运维开发技能，具备排查复杂系统故障的实际经验。
【加分项】
1.有主导过大型企业（尤其是跨国企业）上云和AI平台建设的完整项目经验。
2.熟悉大数据生态（Hadoop, Spark, Flink）与AI平台的结合。
3.对主流AI模型（如大语言模型LLM、CV模型）的部署和优化有实践经验。
4.具备一定的开发能力（Python/Java/Go）。

YOUR TASKS RESPONBILITIES
Lead architects teams through the shift to AI-first, agent-enabled ways of building delivering
Translate horizon scanning on AI emerging tech enterprise strategy, priorities, cross-cutting capabilities
Align senistakeholders on long-term digital direction accelerate responsible innovation at pace
Support communities chapters that spread adoption, learning, shared practice
Network communicate with senistakeholders across enterprises seek opportunities fimprovement
Support at least one community chapter a combination of both
Lead teams including enterprise architects help them understhow to deliver the team’s objectives to meetganizational goals
Carry out horizon scanning across the industry, identifying emerging trends their potential impact opportunity
Support successful delivery of the long-term strategy
Take a leading role in the overall direction of business digital capabilities
Identify priorities fchange to enable delivery at increasing pace
Lead influence the delivery of cross-cutting capabilities that enable change
WHO YOU ARE
Bachelhigher degree in Computer Science, Information Technology, a related field
12+ years experience in IT, with a focus on systems architecture, software development IT process
7+ years experience in a seniIT role, preferably as an Enterprise Architect similar leadership position
Proficiency in IT infrastructure, including cloud computing, networking, databases, application development
Expert knowledge of integration patterns practices
Strategic thinking ability to align IT strategy with business goals
Ability to mentdevelop more juniarchitects IT staff
Capability to driveganizational change foster a culture of innovation
Experience in ensuring that IT systems meet security regulatory requirements
Expert understanding of DevOps practices tools
Extensive experience with microservices architecture RESTful API design
Familiarity with automated testing frameworks tools
Excellent verbal written communication skills in English Chinese
Strong ability to evaluate emerging technologies assess their potential impact
Ability to work collaboratively in a cross-functional team
Ability to build consensus among diverse stakeholders
Hands-on experience designing architecting AI agents (e.g.,chestration patterns, tool use, memory, guardrails, human-in-the-loop workflows)
AI-first mindset: able to reframe business technology problems through the lens of intelligent automation generative AI, not as a bolt-on feature
Deep practical understanding of GenAI capabilities limitations — what it can reliably deliver today, where it fails, how to architect around uncertainty, hallucination, cost, latency, compliance risk
In-depth knowledge of specific technology stacks platforms used in IT
Expertise in API-first integration
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