openai frontend tech phone screen with back-to-back interviews
Interview Experience
Recruiter聊完直接同一天约了两轮back to back面试
第一轮
FrontEnd Coding
给一个视频,就是一个简单的输入框和submit button,然后底下render从AI返回的streaming text,可以想象成一个简易的ChatGPT
35分钟全部搞定,后面都在聊天
第二轮
System Design
设计ChatGPT Playground,含有parameters和presets,前后端都聊,包活server出问题或者model出问题怎么处理都需要聊。
虽然所有的question我都address了但可能因为不够主动挂了,感觉开放爱还是希望candidate自己把所有情况都主动讨论出来而不是面试官提出follow-ups然我们解决。
觉得有用的话求米求米🙏
Full Details
Recruiter聊完直接同一天约了两轮back to back面试
第一轮
FrontEnd Coding
给一个视频,就是一个简单的输入框和submit button,然后底下render从AI返回的streaming text,可以想象成一个简易的ChatGPT
35分钟全部搞定,后面都在聊天
第二轮
System Design
设计ChatGPT Playground,含有parameters和presets,前后端都聊,包活server出问题或者model出问题怎么处理都需要聊。
虽然所有的question我都address了但可能因为不够主动挂了,感觉开放爱还是希望candidate自己把所有情况都主动讨论出来而不是面试官提出follow-ups然我们解决。
觉得有用的话求米求米🙏
About This Question
This is a candidate experience report from a openai interview for a frontend role (newgrad level) during the phone screen round reported in 2026.
It covers the following topics: System Design .
Topics
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About OpenAI Interview Reports
This question was reported by a candidate who interviewed at OpenAI. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.
Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at OpenAI are the higher-signal extractions to take from this report.
For broader preparation context, the OpenAI interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.
How To Practice This Type of Question
Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.
Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in OpenAI reports consistently are the ones worth investing in; one-off niche problems are not.
During Your OpenAI Round
Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.
The single most predictive failure mode in OpenAI reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.