OpenAI L5 Software Engineer Interview Guide

What to expect from coding, system design, and discussions of your technical leadership

Updated Sep 6, 2026

OpenAI's L5 interview combines hands-on engineering with a close look at the technical work you've led. L5 is often compared with Staff-level scope at companies such as Google, although titles vary across candidate accounts. It sits above L4. Prepare for coding and system design alongside conversations about your past projects and how you work with other people.

For Staff candidates, it's worth giving the project and leadership conversations as much preparation attention as the technical exercises. They give you room to explain how you chose a direction, brought other engineers along, and delivered something that mattered beyond your own contribution. Below, we cover the interview format and what candidates from our community found useful to prepare.

The interview process

You'll start with a recruiter or hiring manager conversation about your background and the role. From there, you'll move into the technical assessments. OpenAI uses both live coding interviews and take-home projects, depending on the team. Candidates taking the live-interview route describe coding and system-design screens. With a take-home, you'll build a piece of software on your own, then review and extend it with an engineer.

If those assessments go well, you'll advance to the final loop. Further coding and design conversations sit alongside discussions of work you've led and how you collaborate with other people.

Get the specific round list from your recruiter before organizing your preparation. Set aside time for the assignment if your team uses a take-home. A discussion of your past work may require slides, and leadership and collaboration may be separate conversations. Those details affect what you need to prepare before the final loop.

OpenAI's published interview guide describes four to six hours of final interviews over one or two days, usually virtual, with a San Francisco onsite option. It aims to provide updates within a week after each stage and a decision within a week of the final interviews. References may be requested at that point. Share any competing offer deadline early.

Talking with the recruiter

The first step is a chat with your recruiter or hiring manager. They'll want to hear what you've worked on, why you're considering a move, and what interests you about OpenAI. It's also your opportunity to understand what Staff-level work would look like on the team.

Before the technical rounds, get answers to these practical questions.

• Is this a team-specific process or a broader engineering pipeline, and when is the level decided?
• Will I have live coding, a take-home assignment, or both? What are the take-home deadline and expected hours of work?
• Does the role require a particular programming language, and how long is each coding round?
• What kind of system design should you prepare for, and is there a separate domain interview?
• Does the project discussion require slides, and how much time should you leave for questions?
• Which tools, including AI assistants, are allowed in each round?

The take-home assignment

For teams that use a take-home, it comes after the recruiter conversation and before the live technical interviews. Candidates have described this sequence in both full-stack and platform SWE interviews. You build a working piece of software, then return to it with an interviewer who asks about your decisions and how you'd change the implementation.

You work in your own development setup for the take-home, with your usual editor and local tools. That can include AI coding tools when the assignment permits them. Check the instructions for both the assignment and its live review, since permission to use AI at home doesn't necessarily carry over to the interview. You'll still need to understand, explain, and modify everything you submit.

To get a feel for this kind of assignment, try our open-ended AI coding interviews. You'll build working software in your own editor with your own AI tools, then answer debrief questions about your implementation and receive feedback. It's practice for the same build-and-review format, rather than another timed algorithm question.

Before starting the actual take-home, confirm the expected hours of work as well as the submission deadline. Also check whether your technical deep dive reviews the assignment or a project from your career. Those are different conversations to prepare for.

Coding

The live coding rounds often focus on practical implementation. Think small databases, credit-tracking services, and resumable iterators, with several behaviors to implement. The challenge is often the amount of working code you need to produce within the session. Algorithmic questions still appear, including LeetCode-medium-style problems, so keep those skills in your preparation too. Plan to complete the work without AI assistance.

Data structures still matter. Our Staff reports describe using familiar tools such as hash maps, heaps, sorting, and binary search, with several requirements to satisfy in the same implementation.

"The coding problem question was rather long, use the interviewer to focus on important parts." — OpenAI Staff candidate

LeetCode's Design category is a good place to practice this style of question. Work on completing those implementations within a time limit, including running the tests. Candidates in our reports repeatedly mention how much of the session goes toward getting all the required behavior working.

Candidates report live coding in CoderPad, where you can run code and tests. OpenAI's stated criteria include solution design, code quality, performance, and test coverage. Some screens use a tests-first format. Some SWE loops also include refactoring or debugging existing code, so practice reading and modifying an unfamiliar implementation as well as writing one from scratch.

Can you use AI?

For live coding preparation, assume you'll code without AI assistance. Turn off AI autocomplete and code-generation tools during practice so you're comfortable implementing and debugging the solution yourself.

Use AI only when the instructions for that round explicitly allow it. OpenAI's official policy says tool permissions vary by interview, so your recruiter's instructions and preparation materials take precedence over general advice.

System design

The system-design rounds are working discussions about how you'd build a system. You start from a prompt and develop the design with an interviewer, who can question your choices or introduce constraints as the conversation progresses. Our Staff reports emphasize the depth of those discussions and the need to keep them moving without waiting for the interviewer to direct every step.

For L5 preparation, practice arriving at a coherent design within the session and discussing its internals in enough detail to defend your decisions. Candidates describe follow-ups that reach into how a component actually processes work, not just which database or queue sits in the diagram. That is a reason to study fewer designs more thoroughly, rather than collect a long list of memorized architectures.

Across OpenAI SWE reports, design prompts include a webhook delivery platform, a Slack-like messaging service with a two-week MVP deadline, and a CI/CD system similar to GitHub Actions. Prepare to work within constraints like these while explaining reliability, delivery scope, and operational tradeoffs.

"In your system design interview, plan on taking an example and going through your entire design. Learning to drive system design interviews is key." — OpenAI Staff candidate

The system-design delivery guide can help if you haven't done a timed design interview recently. For practice material, our Job Scheduler and WhatsApp breakdowns cover useful distributed-systems topics. Choose additional problems around the team you're interviewing for. The company name alone isn't a reason to spend your preparation on model training or GPU infrastructure.

The project discussion

The project discussion is where the interview turns to engineering work you've already done. You'll walk through a substantial project, with follow-up questions about the architecture, your decisions, and the outcome. Candidates have described a roughly 30-minute presentation followed by detailed questions, including one account with 15 minutes of Q&A within a scheduled one-hour round. Follow your invitation's duration and leave room for discussion.

Project selection matters at L5. Choose work where you can explain both the technical decisions and your role in getting the project delivered. A project you helped define and lead usually gives you more to discuss than a larger, better-known system where you owned only a small piece.

Our Staff reports highlight personal ownership, alternatives considered, and impact as important preparation topics. To give the interviewer enough context, explain why the work was needed, what was difficult about it, which decisions were yours, and what changed after it shipped. If other teams had to adopt your work or change their plans, that belongs in the discussion too.

Leave room for the questions. A polished summary of the finished architecture won't cover why you rejected another approach, what went wrong during delivery, or what you'd do differently now. Those are worth revisiting before the interview, while you still have time to recover the details.

Leadership and collaboration

The behavioral conversations look at how you work with people, especially when a technical decision involves more than your own team. Leadership and collaboration may have separate slots in the loop, but much of the preparation overlaps.

For Staff, bring examples where you influenced a decision, handled disagreement, or helped other engineers take on work they couldn't have owned before. The useful detail is what you actually did and how others responded. Explaining why a disagreement was reasonable on both sides says more about your judgment than a story where everyone else eventually realized you were right.

Our Staff candidates also recommend preparing examples of failure, ambiguity, and work across teams. You don't need a different story for every possible question, but you do need enough range that every answer isn't the same successful launch.

You should also have a considered answer to why you want to work at OpenAI. Read its Charter and the team's recent work, then connect your interest to the role you're discussing. There's no need to turn an engineering career conversation into a rehearsed speech about AGI.