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Open nowPosted 105 days ago

【2027届秋招】AI测试工程师(web平台)

moonton/campus92 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【2027届秋招】AI测试工程师(web平台)moonton/campus · Shanghai, Chinese Mainland
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The clock on this job

Early applications get read.

13.9% of postings close within 7 days. Measured by our own scanner across the market. moonton/campus postings stay open a median of 15 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.9%7 days
  4. 22.4%14 days
  5. 38.1%30 days
  6. 59.0%60 days
This job: posted 105 days ago

moonton/campus median: 15 days open

The posting

我们希望招聘的不是只负责执行测试用例、发现产品缺陷的传统测试工程师,而是具备工程思维、质量意识和技术潜力的质量工程人才; 你将从业务测试和交付质量保障出发,逐步参与测试工程能力、AI 测试能力、质量度量与治理机制的建设。长期来看,你将有机会成长为质量体系的构建者,以及能够深入业务现场、结合工程能力解决复杂质量问题的质量领域 FDE(Forward Deployed Engineer); 作为校园招聘岗位,我们不要求你已经具备成熟的质量体系建设经验,但希望你具备良好的技术基础、问题分析能力和持续学习潜力。

岗位职责: 一、业务质量保障 1. 参与产品需求分析、技术方案评审和测试方案设计,识别需求中的缺失、歧义、冲突及潜在质量风险; 2. 负责功能、接口、兼容性、性能、稳定性等测试工作,保障需求按计划、高质量交付; 3. 结合业务链路、系统架构和用户场景,设计有效的测试策略,而非简单执行既定用例。 二、测试工程能力建设 1. 参与接口自动化、UI 自动化、测试数据构造、流量回放、质量巡检等测试工具或平台的建设; 2. 通过脚本、工具和工程化方法减少重复劳动,提升测试覆盖率、执行效率和结果可信度; 3. 参与测试资产、测试标准和工程实践的沉淀,使测试能力能够被复用和持续演进。 三、AI 测试能力探索 1. 探索大模型及 Agent 在需求分析、测试设计、自动化生成、测试执行、缺陷分析等场景中的应用; 2. 参与 AI 测试工具、Skill、Agent 或 Harness 能力的设计、开发、评测和优化; 3. 建立对 AI 生成结果的准确性、稳定性、采纳率、误报率等效果评估意识,推动 AI 能力从 Demo 走向实际业务应用。 四、质量分析与治理 1. 参与交付质量、线上问题、缺陷分布和研发过程数据的分析,识别质量问题的共性规律和根因; 2. 协同产品、研发及相关团队,通过流程、规范、工具和技术方案推动问题解决; 3. 逐步参与质量指标、风险识别机制和质量治理体系建设,推动质量保障从交付末端向研发全流程延伸。

1. 2027届本科及以上学历,计算机、软件工程、人工智能、信息安全、数学等相关专业优先; 2. 具备扎实的计算机基础,了解数据结构、计算机网络、操作系统、数据库及软件工程基本知识; 3. 掌握至少一门编程语言,如 Python、Java、JavaScript、Go、C++ 等,能够独立完成基础编码和问题调试; 4. 具备良好的逻辑分析能力,能够将复杂问题进行拆解、定位和验证; 5. 对软件质量、工程效率或 AI 技术有兴趣,愿意深入理解系统实现,而不满足于完成表面测试; 6. 具备较强的责任意识、沟通协作能力和主动学习能力,能够推动问题形成闭环; 7. 能够接受从业务测试实践出发,逐步向测试工程、AI 测试及质量治理方向发展。

加分项 1. 有测试开发、软件开发、AI 应用、数据分析或开源项目实践; 2. 熟悉接口测试、自动化测试、持续集成、性能测试或稳定性测试中的一种或多种; 3. 使用过大模型 API、Agent、RAG、MCP、Prompt Engineering 等相关技术,并有实际项目经验; 4. 了解软件研发流程、DevOps、可观测性、微服务或云原生相关技术; 5. 参加过程序设计、软件测试、人工智能、数学建模、CTF 等竞赛; 6. 有较强的问题意识,能够主动发现现有流程或方案中的不足,并尝试通过技术手段解决。

我们看重的潜力 1. 质量意识,不仅关注功能是否正确,也关注系统是否稳定、过程是否可靠、问题是否能够被长期解决; 2. 工程思维,愿意通过代码、工具和系统化方法解决重复性、规模化问题; 3. 分析能力,能够从现象出发定位根因,而不是停留在问题表面; 4. AI 素养,理解 AI 能力的价值与边界,能够对生成结果进行验证、评测和持续优化; 5. 业务理解,能够进入真实业务场景,在约束条件下设计可执行的质量解决方案; 6. 成长潜力,愿意从测试执行者逐步成长为质量工程师、质量体系构建者和质量领域 FDE。

发展方向,入职后,你将根据个人能力和兴趣,逐步向以下方向发展 1. 业务质量与复杂系统测试; 2. 测试开发与质量工程平台; 3. AI 测试 Agent 与 Harness; 4. 稳定性、性能与可靠性工程; 5. 质量度量、分析与研发过程治理; 6. 质量领域 FDE 与综合质量解决方案。

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