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Tencent Holdings · Guangzhou

# 企业微信-企业客户AI解决方案

Guangzhou Sales 

Listed on Tencent Holdings’s official careers site. Listed as of October 19, 2026. Check that it is still open and apply there.
[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=2100068989031067648)

[OpenNash Jobs](https://jobs.opennash.com/) / [Tencent Holdings](https://jobs.opennash.com/companies/tencent-holdings/) / 企业微信-企业客户AI解决方案

## Job description

### 客户调研与场景挖掘
- 深入中腰部客户业务一线，调研真实业务流程与痛点，从中识别能用 AI 解决的高频场景；

### AI 方案交付落地
- 基于企业微信+AI能力（智能表格、机器人、workbuddy等）完成方案配置与上线，对使用和转化等交付结果负责；

### 打法沉淀与批量复制
- 把单点客户的成功打法提炼成标准化方案包和交付SOP，推动中腰同行业客户的高效、批量复制；

### 转化协同
- 配合网销/商务团队，用AI 场景案例支撑批量转化（商业产出、方案讲解、标杆案例、直播出镜等）；

### Al 能力反哺
- 沉淀客户侧高频 AI需求，反哺内部产品与方案迭代。 Requirements
- 要求；
- 本科及以上学历，2年以上B 端客户成功、解决方案或交付实施经验，有 SaaS/企业服务批量交付经验者优先；

### 有 Al sense
- 日常高频使用AI工具解决真实工作问题，理解大模型/Agent能力边界，能快速判断结合落地；

### 场景挖掘能力强
- 能通过访谈和数据分析快速摸清一个陌生行业的业务流程，从杂乱需求中识别共性场景；

### 动手落地能力强
- 能独立完成产品配置、Prompt调试、简单接口排障，把方案装进客户业务里；
- 多客户并行管理能力强，节奏感好，适应线上线下高频次客户沟通；
- 沟通直接，能把技术语言翻译成客户听得懂的业务语言。

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Oct 12, 2026
- Last checked: Oct 19, 2026
- Listed for: 7 days
- Location: Guangzhou[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=2100068989031067648)

## More jobs at Tencent Holdings

### [企业微信-商务拓展经理-工业行业（深圳）](https://jobs.opennash.com/companies/tencent-holdings/jobs/371fce897de2fecd62b6/)

Guangzhou

### [企业微信-商务拓展经理-零售行业（北京/上海/深圳）](https://jobs.opennash.com/companies/tencent-holdings/jobs/1ad4d5d5fbd85619ff81/)

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### [企业微信-商务拓展经理-餐饮/文旅酒店行业（北京）](https://jobs.opennash.com/companies/tencent-holdings/jobs/4b4c16b035a223ff3f64/)

Guangzhou

### [企业微信-客户成功-行业解决方案专家（KA）（北京/深圳/上海）](https://jobs.opennash.com/companies/tencent-holdings/jobs/34382f7a42293bf38cb2/)

Guangzhou

### [企业微信-生态合作经理-硬件方向](https://jobs.opennash.com/companies/tencent-holdings/jobs/d7c24dd25cff87109fb3/)

Guangzhou

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Dates come from the employer where stated; “first seen” and “last checked” are our own observations.

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