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Shao MengUpdated Oct 30 14:33

OpenAI Software Engineer Interview Process Retrospective: Including an Optional Agentic Coding Round

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A 2026 OpenAI SWE interview retrospective shows that the process includes a recruiter screen, two technical screens of about 60 minutes each on the same day, a take-home assignment of about 48 hours, a technical deep dive that probes the code line by line, and 4 onsite rounds. The onsite coding includes a progressive multi-part problem (such as token-level streaming diff and rollback), and the system design question is "Design ChatGPT," involving GPU allocation and autoscaling under non-stationary traffic. There is also an optional fifth round, Agentic Coding, in the beta stage, which requires using an AI coding agent to handle problems in large codebases that are difficult to address by hand.

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OpenAI 软件工程师面试实录

转自 Reddit r/InterviewCoderHQ, 一份 2026 年 OpenAI SWE 面试的个人复盘:流程比一般大厂更强调「能落地的系统题 + 带回家作业 + 对着代码逐行追问」,现场还有渐进式多段编码;另有可选的 Agentic Coding(用 AI 编程助手啃太大、手写扛不住的题)。

# 流程概览

1. 招聘筛选(Recruiter Screen) 偏轻松的背景聊天。被问到对 AI 未来的看法;建议事先读 OpenAI 的 Charter。

2. 技术筛选(同一天两场,各约 60 分钟) · 编码:做一个带版本的键值存储(versioned key-value store)。 · 系统设计:带容错的任务调度器(job scheduler with fault tolerance)。

3. 带回家作业(Take-Home,约 48 小时) 要求「做真东西」:分布式 webhook 投递系统,含重试与死信队列(dead-letter queues)。

4. 技术深挖(Technical Deep Dive) 面试官先通读作业,再列清单,对着代码逐行走:每个选择、每个决策都可能被问到。

5. 现场环节(Onsite Loop,共 4 轮)

编码 1:渐进式多段题,每一段要先做出能跑的版本,才开下一段。题例是 token 级流式 diff,要跟踪状态变化并支持回滚。建议:先尽早做出正确版本,再迭代。

编码 2:更偏系统味,状态管理、并发、内存效率;还考到 Python 内部机制,例如生成器、async、迭代器。

系统设计:题目是「设计 ChatGPT」。关注点包括 GPU 分配、非平稳流量下的自动扩缩、分布式协调。建议把模型服务层抽象出来;行为面准备技术领导力、跨多团队的架构决策、压力下达成共识的故事,并给出具体权衡,不要空泛软技能话术。

6. Agentic Coding 轮(beta,可选第五轮) 给一个很大的代码库和「靠手写啃不动」的问题,期望用 AI coding agent 来解。

Source

Shao Meng