OpenAI Interview Questions and Process: How to Prepare (2026)

The short answer: OpenAI’s own interview guide describes five stages: an application review (typically a week), introductory calls, a skills-based assessment that varies by team, final interviews of 4 to 6 hours with 4 to 6 people over 1 to 2 days, and a decision within about a week. It says it’s less interested in credentials than in how you think, how you communicate and whether you care about its mission. Whether you can use AI tools depends on the interview, and your preparation materials will tell you. interviewing.io, drawing on conversations with OpenAI engineers, reports practical, multi-part coding problems rather than puzzles, system design rounds, a presentation on a past project and behavioral rounds. Prepare by reading OpenAI’s Charter and recent work, practicing practical coding, and having an honest view on AI safety.

We aren’t affiliated with OpenAI. Process details below come from OpenAI’s published guide. Where we rely on other reports, we say so, and OpenAI notes that your experience may differ by team and role.

What OpenAI says about its interview process

You should also hear within a week whether you’ve moved on after the assessment, and OpenAI says the recruiting team will give you preparation material for it.

What OpenAI looks for

OpenAI’s guide is unusually direct about this:

• Not credentials. It says it isn’t credential-driven and wants to understand your background and what you can contribute.
• Experts or high potential. It hires people who are already experts and people who’ve shown they can ramp up quickly in a new domain and produce results.
• How you work with others. It names collaboration, effective communication, openness to feedback, and alignment with its mission and values.
• How you think. It says interviews are designed to show how you approach problems, make decisions and communicate your reasoning.
• For engineers, it generally looks for well-designed solutions, high-quality code, optimal performance and good test coverage.

The final interviews focus on your area of expertise and, in OpenAI’s words, are designed to stretch you beyond your comfort zone. Expect to be pushed past what you know, and treat that as part of the test.

Can you use AI tools in an OpenAI interview?

It depends on the round. OpenAI says some formats intentionally allow AI and other tools, while others are designed to assess your independent problem solving without them. It explains what’s allowed in your preparation materials, and tells you to ask your recruiter if you’re unsure. Do that before the interview rather than guessing.

interviewing.io goes further, saying AI use is prohibited except in a beta agentic coding round. Not all candidates get that round. It has you change an existing codebase with an AI coding agent, because the problem is too large to do by hand. If you might get one, practice directing an agent and reviewing what it produces, and treat your preparation materials as the final word.

OpenAI’s mission and values

OpenAI’s stated mission is to ensure that artificial general intelligence benefits all of humanity. Its Charter sets out four principles: broadly distributed benefits, long-term safety, technical leadership and cooperative orientation.

Its careers page lists four values (humanity first, act with humility, feel the AGI, ship joy) and four operating principles (find a way, creativity over control, update quickly, intense focus). Prepare stories that show the behavior behind them, not the slogans. “Update quickly”, for example, is a question about the last time you changed your mind.

In October 2026, Fortune reported that OpenAI was piloting a “mission interview”, starting with the marketing and human resources teams. Candidates talk about how they’d contribute to the mission, with an interviewer from a different team. An OpenAI representative told Fortune there’s no “right” answer and that skepticism and disagreement are welcome. It’s a pilot, so ask your recruiter whether it applies to you.

What’s reported about the engineering rounds

OpenAI doesn’t publish its round-by-round format for each team. interviewing.io, which says its information comes from conversations with OpenAI engineers, describes the software engineering process as decentralized, varying by team, and typically including:

• A recruiter call of about 30 minutes on your experience, interest and goals. interviewing.io advises not sharing salary expectations at this stage.
• A technical phone screen of about an hour in CoderPad, covering practical algorithms and data structures.
• A system design screen of about an hour in Excalidraw.
• Final interviews with coding, system design, a roughly 45-minute presentation on a challenging technical project (with slides), a behavioral conversation with a senior manager, and a team behavioral interview.
• An overall timeline of about six to eight weeks.

It describes the coding as more practical than typical algorithm puzzles, and multi-part, with about four parts. Its advice is to get a clean working solution for the core parts first. Topics it lists include trees, binary search, graphs, time-based data structures, versioned data stores, coroutines and object-oriented design. It also reports some math-heavy coding questions from information theory and probability, such as KL divergence and cross entropy.

For system design, it reports practical prompts such as designing Yelp, Twitter or a notifications system, with follow-ups on scalability, reliability and trade-offs. It warns that if you name a specific technology, you should be ready to go into detail on it.

Treat these as reports, not rules, and ask your recruiter what your loop includes.

Practice questions by round

We wrote these to match the formats above. They aren’t leaked questions.

Recruiter and motivation

• “Why OpenAI, and why this team?”
• “Which recent OpenAI release or paper interested you most? What would you change about it?”
• “What kind of work do you want to be doing in two years?”

Practical coding

• “Build an in-memory key-value store that returns the value of a key at a given timestamp.”
• “Implement a rate limiter, then extend it to handle many users.”
• “Write an iterator you can pause, save and resume.”

System design

• “Design a service that streams model responses to millions of users.”
• “Design rate limiting and usage-based billing for an API.”
• “Design a system that compares a new model against the current one before release.”

Project presentation

• “What was the hardest technical decision on this project, and what did you reject?”
• “What broke, and how did you find out?”
• “What would you build differently today?”

Behavioral

• “Tell me about a time new information changed your mind.”
• “Tell me about shipping something imperfect on purpose.”
• “Tell me about a disagreement between research, product or safety priorities. How did it end?”

Mission and judgment

• “What worries you most about advanced AI?”
• “When should a company delay a launch because of safety concerns?”
• “Where do you disagree with OpenAI?”

A practice coding problem: a resumable iterator

Here’s one worked example in the practical style reported above. Build a basic version first, then add to it.

class ResumableIterator:
    def __init__(self, items):
        self.items = items
        self.pos = 0

    def __iter__(self):
        return self

    def __next__(self):
        if self.pos >= len(self.items):
            raise StopIteration
        value = self.items[self.pos]
        self.pos += 1
        return value

    def get_state(self):
        return {"pos": self.pos}

    def set_state(self, state):
        self.pos = state["pos"]

We ran this on Python 3.12 with tests for saving, resuming, running to the end and empty input. In an interview, the follow-ups are where it gets interesting: what if the iterator reads several files, what if the data changes between save and resume, and how would you test it? Say those out loud, and write the tests. OpenAI says it looks for good test coverage. Our Python interview questions cover the language.

How to answer “Why OpenAI?”

What they’re listening for: a specific reason that would still be true without the brand name.

Example: “I’ve spent three years building evaluation tooling, and the most useful thing I’ve read recently was your team’s work on measuring model behavior before release. I want to work on that problem at a place where the results change what ships. I also think the Charter’s concern about a race without time for safety is the right one to worry about, and I’d like to work where people argue about it openly.”

Avoid: “It’s the most exciting company in AI”, or praising a product without saying what you’d do there. More on why you want to work here.

How to prepare, step by step

1. Do the reading OpenAI recommends. Its guide lists the Charter, its research publications and blog posts, plus the Deep Learning Book and Spinning Up in Deep RL for technical roles. It suggests focusing on recent updates related to your team.
2. Ask your recruiter exactly what’s in each round, including which tools are allowed and what language you can use.
3. Practice multi-part, practical coding. Time yourself, get the core working, then extend it, and write tests as you go.
4. Practice system design out loud, including scale, reliability and trade-offs. Our system design guide has a framework.
5. Build your project presentation around one hard problem: the options, the trade-offs, your own contribution, the result and what you’d change. interviewing.io says slides are expected.
6. Write stories against the values and principles, in STAR order (situation, task, action, result). Our STAR method guide has examples.
7. Form your own view on AI safety. interviewing.io says to expect questions on ethics and safety. You don’t need to agree with OpenAI, but you do need to have thought about it.

By role

• Software engineers: the rounds above, with heavy weight on practical coding and test quality.
• Research engineers and scientists: OpenAI says final interviews focus on your area of expertise, so be ready to go deep on your papers, experiments, machine learning fundamentals and the math behind your work. Our LLM engineer questions and AI engineer questions cover the technical ground.
• Product and business roles: formats vary by team, so ask your recruiter what to expect. Prepare product judgment and how you’d work with researchers. The mission interview pilot started with marketing and HR.
• Every role: OpenAI’s guide says to be ready to discuss your experience, motivations and goals, and to know the work most related to your team.

Questions to ask your interviewers

• “How does this team decide what to ship and what to hold back?”
• “What’s changed about this team’s work in the past six months?”
• “How do researchers, product and safety teams resolve disagreements here?”
• “What does someone do in their first 90 days to be seen as successful?”

Our full list of questions to ask the interviewer has more.

Practice explaining your thinking out loud

See how other employers hire in our company interview guides, including our Anthropic interview guide.

Frequently asked questions

Sources

• OpenAI, Interview guide, Charter and Careers. Read on 10 November 2026.
• interviewing.io, OpenAI’s Interview Process & Questions. Read on 10 November 2026.
• Emily Forlini, OpenAI is piloting a ‘mission interview’ for candidates, Fortune, 5 October 2026. Read on 10 November 2026.