OpenAI interview guide: practise the real format first
OpenAI's coding rounds look less like LeetCode and more like a normal day of engineering work. You get a practical problem with several parts, a codebase-style setup, and an interviewer who wants working, readable code at a fast pace. Senior candidates also face a long walkthrough of a past project, and that round is where many loops are decided. A mock interview with an engineer from a top AI or product company is the quickest way to get used to that format before it counts.
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This guide is compiled from OpenAI's published interview guide and candidate reports from 2025 and 2026. The practice questions are written in the style candidates describe. None of them are leaked.
OpenAI interview process at a glance
[[table]]
Stage | Format | Length
Recruiter call | Background, motivation | 30 min
Technical screen | Coding or design | 60 min
Second screen | Coding, design or take-home | 60 min+
Final loop | 4 to 6 interviews | 4 to 6 hrs
Team match | Level and team | Varies
[[/table]]
OpenAI's own guide says final interviews usually take four to six hours with four to six people, spread across one or two days, and they're virtual by default with an option to come onsite in San Francisco. The exact mix of rounds changes by team, so ask your recruiter which version you'll get. Most candidates report the whole process taking four to eight weeks.
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The OpenAI interview rounds, one by one
Recruiter call
A 30-minute conversation about your background and why you want to work at OpenAI. Take the "why OpenAI" question seriously. Several 2026 reports mention being asked why OpenAI over other AI labs, and a generic answer about AI being exciting won't stand out. Talk about a product, a research result or a safety problem you actually care about.
Technical screens
Most software engineers get one or two screens before the final loop. One recent report described a coding screen plus a system design screen. Other teams use a take-home project or a pair-programming session instead.
The coding problems tend to be practical and multi-part. Instead of a single algorithm puzzle, you might build a small in-memory store, then add features step by step as the interviewer reveals new requirements. Speed matters. Candidates who passed say they finished most parts and kept their code clean enough to extend.
Final loop
A typical software engineering loop has four to six interviews. Candidates commonly describe these:
- Coding. Another practical, multi-part problem, sometimes in a real editor with files and tests.
- System design. A large-scale design, often with an AI flavour like serving model requests, rate limiting an API or building an evaluation pipeline.
- Project deep dive. You walk through a system you built, and the interviewer digs into decisions, trade-offs and what went wrong. This is the round candidates single out most.
- Behavioural and mission. How you work with others, handle disagreement and think about building AI safely.
Some teams have their own rules about using AI tools in interviews, and the policy has shifted over time. Confirm with your recruiter before each round.
What changes by level
[[table]]
Level | Focus | Deciding round
New grad | Coding speed | Coding
Mid-level | Coding + design | Design
Senior | Design + ownership | Project deep dive
Staff+ | Direction, scope | Deep dive + design
[[/table]]
Senior and staff candidates often go through the same loop, and OpenAI sets the level at the end rather than up front. Strong candidates then move into team matching. That means your project deep dive and design answers do double duty: they decide whether you get an offer and at what level.
For experienced engineers, the deep dive is worth the most prep time. Pick one system you know inside out. Be ready to explain the architecture, the numbers (traffic, latency, cost), the hardest bug, and what you'd change if you rebuilt it today.
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OpenAI practice questions
These are practice questions in the style candidates describe. They're not leaked questions.
Coding
- Build a key-value store with get, set and delete. Then add transactions that can be rolled back. Then add a time-to-live on keys.
- Given a list of API requests with timestamps, implement a rate limiter per user. Then make it work across several servers.
- Write a function that resolves a new directory path from a current path and a relative path like ../a/./b.
System design
- Design the backend for a chat product that streams model responses to millions of users.
- Design a system to run nightly evaluations of a model on thousands of test sets and report regressions.
- Design usage-based billing for an API with strict per-customer limits.
Behavioural
- Why OpenAI, and why this team?
- Tell me about a time you shipped something quickly and later had to fix its quality.
- Tell me about a decision where safety or reliability slowed a launch. What did you do?
Practise these with an engineer and get scored
How to prepare for an OpenAI interview
Change how you practise coding. Pick problems that grow in stages, like a key-value store, a file system or a job scheduler, and build them in a plain editor against a timer. After each stage, check that your code is still easy to extend. That's closer to what OpenAI tests than a list of isolated puzzles.
Learn how AI products are built. You don't need to be an ML researcher for a software role, but you should be comfortable talking about streaming responses, token limits, caching, rate limits, evaluations and cost per request. If you've built something with an LLM API, have it ready to discuss.
If you're experienced, prepare your deep dive like a talk. Draw the architecture from memory, know your numbers, and practise answering "why didn't you do X instead?" without getting defensive.
Finally, run at least one full mock loop with someone who'll push back. The practical coding pace and the deep dive are both hard to judge on your own.
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FAQs
How many rounds are in the OpenAI interview? Most software engineers report six to eight conversations in total: a recruiter call, one or two technical screens, and four to six final interviews.
Does OpenAI ask LeetCode questions? Some screens include classic problems, but most coding rounds are practical and multi-part, closer to real engineering work.
Is the OpenAI interview virtual? Yes, by default. OpenAI says candidates can choose to interview onsite in San Francisco.
How does OpenAI decide my level? Usually at the end of the loop, based mostly on your design and project deep dive feedback. Team matching comes after.
Can I use AI tools during an OpenAI interview? It depends on the team and the round. Ask your recruiter before each interview.
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Get Ready for OpenAI's Practical Loop: Take a Mock Interview
OpenAI's rounds reward engineers who can build fast, explain their choices and go deep on their own work. Practise that with an engineer from a top tech company, get a scorecard for each round, and find out where you'd be levelled before the real loop.
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