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岗位职责: Job Description: 1、业务场景与产品设计:参与真实业务需求分析,梳理用户目标、任务流程与成功标准,判断适合引入 AI 的环节;围绕模型能力设计产品功能、交互方式与人机协作流程。Business & Product Design: Analyze business needs and user workflows, identify AI opportunities, and design AI-driven features and human-AI collaboration.2、Agent 开发与系统集成:在团队指导下,使用 Python 或 JavaScript/TypeScript 开发可运行的 Agent 原型,参与提示词与上下文设计、工具调用、知识检索及任务编排,对接业务 API 和数据源,推动实际场景落地。Agent Development & Integration: Develop Agent prototypes with Python or JavaScript/TypeScript, including prompts, tool calling, knowledge retrieval, task orchestration, and API integration.3、AI Native 产品设计:参与从原型到可用产品的迭代,设计任务进度、结果呈现、用户确认、失败重试与人工接管等交互;关注模型不确定性、数据权限和操作边界,提升任务完成率与用户信任。AI-Native Product Design: Design AI-native workflows and interactions, covering task progress, results, retry, and human handover, while addressing model uncertainty and data permissions. 4、评估与持续迭代:整理真实案例与测试集,结合用户反馈和运行记录,评估输出质量、任务成功率、响应时延与调用成本;跟进新模型、新工具与相关产品,通过小规模实验验证价值并沉淀可复用方案。Evaluation & Iteration: Evaluate AI quality, task success rate, latency, and cost; test new models and tools and turn validated solutions into reusable practices.教育背景:Educational Background:本科,专业不限一周出勤4-5天,能尽快到岗,可以实习6个月优先特定专业知识:Specific Expertise: 1、具备 Python 或 JavaScript/TypeScript 编程基础,能够调用 API、处理结构化数据,使用 Git 并完成基础调试;愿意动手搭建和迭代可运行的应用原型。Programming: Basic Python or JavaScript/TypeScript skills; familiar with APIs, structured data, Git, and basic debugging. 2、了解 LLM 应用的基本原理,对提示词、上下文管理、工具调用(Function Calling)和检索增强生成(RAG)有基本认识;能够通过实践理解模型的能力边界与常见失败方式。LLM Knowledge: Basic understanding of LLM applications, including prompting, context management, Function Calling, and RAG; able to explore model capabilities and limitations through practice. 3、具备产品意识,能从用户目标出发拆解需求,思考 AI 如何改变任务流程与交互方式;能够定义可验证的效果标准,并根据测试结果和用户反馈持续改进。Product Mindset: Able to understand user needs, identify AI opportunities, define measurable outcomes, and iterate based on testing and feedback. 4、学习主动,能够阅读技术文档、快速验证想法并清晰表达过程与结论;愿意使用 AI 编程工具提高效率,并对生成代码进行理解、测试和验证。Learning & Execution: Proactive learner with strong documentation and communication skills; willing to use AI coding tools and validate generated code through testing and review. 5.基础的英语技能
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您目前还没有登录:立即登录岗位职责: Job Description: 1、业务场景与产品设计:参与真实业务需求分析,梳理用户目标、任务流程与成功标准,判断适合引入 AI 的环节;围绕模型能力设计产品功能、交互方式与人机协作流程。Business & Product Design: Analyze business needs and user workflows, identify AI opportunities, and design AI-driven features and human-AI collaboration.2、Agent 开发与系统集成:在团队指导下,使用 Python 或 JavaScript/TypeScript 开发可运行的 Agent 原型,参与提示词与上下文设计、工具调用、知识检索及任务编排,对接业务 API 和数据源,推动实际场景落地。Agent Development & Integration: Develop Agent prototypes with Python or JavaScript/TypeScript, including prompts, tool calling, knowledge retrieval, task orchestration, and API integration.3、AI Native 产品设计:参与从原型到可用产品的迭代,设计任务进度、结果呈现、用户确认、失败重试与人工接管等交互;关注模型不确定性、数据权限和操作边界,提升任务完成率与用户信任。AI-Native Product Design: Design AI-native workflows and interactions, covering task progress, results, retry, and human handover, while addressing model uncertainty and data permissions. 4、评估与持续迭代:整理真实案例与测试集,结合用户反馈和运行记录,评估输出质量、任务成功率、响应时延与调用成本;跟进新模型、新工具与相关产品,通过小规模实验验证价值并沉淀可复用方案。Evaluation & Iteration: Evaluate AI quality, task success rate, latency, and cost; test new models and tools and turn validated solutions into reusable practices.教育背景:Educational Background:本科,专业不限一周出勤4-5天,能尽快到岗,可以实习6个月优先特定专业知识:Specific Expertise: 1、具备 Python 或 JavaScript/TypeScript 编程基础,能够调用 API、处理结构化数据,使用 Git 并完成基础调试;愿意动手搭建和迭代可运行的应用原型。Programming: Basic Python or JavaScript/TypeScript skills; familiar with APIs, structured data, Git, and basic debugging. 2、了解 LLM 应用的基本原理,对提示词、上下文管理、工具调用(Function Calling)和检索增强生成(RAG)有基本认识;能够通过实践理解模型的能力边界与常见失败方式。LLM Knowledge: Basic understanding of LLM applications, including prompting, context management, Function Calling, and RAG; able to explore model capabilities and limitations through practice. 3、具备产品意识,能从用户目标出发拆解需求,思考 AI 如何改变任务流程与交互方式;能够定义可验证的效果标准,并根据测试结果和用户反馈持续改进。Product Mindset: Able to understand user needs, identify AI opportunities, define measurable outcomes, and iterate based on testing and feedback. 4、学习主动,能够阅读技术文档、快速验证想法并清晰表达过程与结论;愿意使用 AI 编程工具提高效率,并对生成代码进行理解、测试和验证。Learning & Execution: Proactive learner with strong documentation and communication skills; willing to use AI coding tools and validate generated code through testing and review. 5.基础的英语技能
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