1p3a Experience · May 2026

openai fulltime software engineer tech phone screen experience

SWE Phone Screen newgrad
1 upvote 17 replies

Interview Experience

system design: design sora 面试官其实就是非常注重各种failure model你怎么说。我问他大概什么DAU 他都不care,说你看着来吧lol。 面试官整体比较严肃,但是也会点头+make sense去肯定,整体还行Code: GPU credit II 小哥真的太好了, 我太紧张了heapq以为是import collections,他说这个lib问题你别管了 我来给你改好。。27min就全部写完了,后面就聊了一下 可能的性能优化 小哥结束说u did a really great job面试完2天之后早上我followup了一下,hr发了move forward 地理帮助非常大,发面经给onsite攒攒rp!!!

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About This Question

This is a candidate experience report from a openai interview for a swe role (newgrad level) during the phone screen round reported in 2026.

It covers the following topics: System Design .

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.