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Open nowPosted 73 days ago

Agent开发工程师

everfir/index8 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen nowAgent开发工程师everfir/index · Shenzhen, Guangdong, Chinese Mainland

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 73 days ago

The posting

我们是谁 我们是一支正在探索 AI 原生应用的创业团队，从 AI 视频生成切入，不到半年已经做出过获得全球百万注册用户、并产生实际千万美金ARR收入的产品。 我们正在研究一个更具挑战的问题：能否让 Agent 不只辅助工程师写代码，而是理解一个真实应用，发现和完成迭代，并通过自动化验证判断结果是否可靠。我们的目标，是逐步减少应用迭代过程中对人工执行和人工验收的依赖。 你将负责什么 设计并实现由 Agent 驱动的应用迭代闭环：理解任务、修改系统、验证结果、分析失败并继续改进； 建立 Agent 的评测体系，用可重复的任务和指标衡量完成质量、回归风险、执行效率、成本及人工介入程度； 研究模型与 Agent 的能力边界，并通过上下文工程、工具设计、环境反馈、流程约束、测试与可观测性提升其表现； 将业界最新的模型和 Agent 能力接入真实业务系统，用实际结果判断它们在哪些环节有效、为什么失效，以及如何变得更可靠； 从一次失败中提炼可复用的工程机制，让一类问题被系统性解决，而不是不断增加针对单个案例的补丁。

我们需要这样的你 有扎实的工程背景，前端、后端或客户端方向不限；理解计算机基础，具备系统设计和架构设计能力； 有真实业务开发经历，理解需求变化、复杂状态、历史兼容、线上故障和交付质量等具体难题。除非有非常突出的相关成果，否则这是硬性要求；有 C 端应用经验更佳； 熟练使用 Coding Agent 完成复杂工程任务，不只追求“能生成代码”，还会判断 Agent 擅长什么、不擅长什么，并能针对限制设计工程解法； 能构建可信的评测方法，不用少量成功案例代替稳定性判断，能够通过任务集、执行轨迹、结果验证和回归测试持续衡量 Agent； 具备从具体问题向上抽象一层的能力：能识别多个问题背后的共同结构，形成批量、长期有效的解法，同时愿意回到事实验证自己的判断； 能独立把模糊问题推进为可运行、可验证的系统，并对最终效果负责。 如果你做过以下事情，会是明显加分项：构建或深度改造过 Coding Agent / Agent 工作流；建立过 Agent Benchmark 或自动评测系统；让 Agent 在真实代码库中稳定完成过一类任务；有复杂 C 端产品、开发工具、测试平台、CI/CD 或可观测性系统经验。 你将获得 直接参与一个仍处在早期、但会深刻改变软件生产方式的问题：应用如何在尽量少的人类介入下持续进化； 在真实产品和真实代码库中验证想法，而不是停留在 Demo、论文复现或提示词实验； 足够大的问题空间和决策权让你尽情发挥，从任务定义、系统设计、实现到评测闭环完整负责； 与团队共同接触和验证最新模型能力，并把有效方法沉淀为长期可复用的工程系统；

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