That may sound daunting, and the stakes are high. Luckily, so are the rewards. In 2025, OpenAI awarded substantial one-time retention bonuses to roughly one-third of its workforce. All software engineers received $1.5 million, while top researchers also secured multi-million-dollar awards. This move underscored just how the company values and protects its talent.

Whether you are a senior level engineer or an emerging developer with strong problem-solving skills, preparing for an OpenAI interview means committing to a tough process. 

This guide is here to help you navigate the OpenAI software engineer interview from start to finish. We’ll walk through each stage of the process, take a close look at the kinds of questions you can expect, point out  common mistakes that can cost you the offer,  explain what happens after your interviews, and share strategies to sharpen your prep. Whether you’re aiming for an entry-level SDE role or bringing experience to a mid-level position, this article will give you the tools to tackle your interviews with confidence.

Table of Contents 

• The OpenAI Interview Process and Timeline
• Common OpenAI Software Engineer Interview Questions 
• Mistakes to Avoid During OpenAI Interviews 
• What Happens After the OpenAI Interview?
• FAQ
• Conclusion

The OpenAI Interview Process and Timeline

The OpenAI interview process consists of four steps: the recruiter call, the technical phone screen, a possible second technical screen depending on the role and the onsite. The recruiter call will last about 30 minutes, the technical phone screen will last about 60 minutes. And the onsite lasts 4-6 hours spread across 1 to 2 days. 

The OpenAI hiring process is decentralized with many differences in interview steps depending on the role you’re applying for. The technical assessment can be anything from an asynchronous coding test - for which they use Hackerrank to a take-home assignment. For live interview OpenAI uses CoderPad. 

Recruiter Call 

The recruiter call is the first step in your OpenAI interview process, but it's not much different from any other recruiter call. The recruiter will ask you questions like why you want to work at OpenAI and previous academic experience, what your previous experience is, and what your salary expectations are. It’s important to not mention too much about your salary expectations and your history because of negotiations further down the line. Do ask your recruiter what to expect of the rest of the hiring process, seeing as there's a lot of variance depending on which team you're interviewing with.

Technical Phone Screen 

Once you’ve passed the recruiter call you’ll move on to the technical round. Since the technical assessment varies from team to team it can be anything from an asynchronous coding test to a take-home assignment. Depending on the role you’re applying for you may be asked to complete more than one assessment. Within a week OpenAI lets you know wether or not you’ve progressed to the next round. 

Onsite 

If you progress to the onsite stage, which takes place virtually,, you can expect several interview rounds in a single day. Interviews are focussed on your area of expertise and are designed to pull you out of your comfort zone, according to OpenAI’s interview guide. 

The loop varies depending on the role and level you’re applying for but generally there’s a behavioral interview with a hiring manager, a presentation, one hour of coding, a system design round for which you’ll use Excalidraw and a behavioral round focused on working with teams. 

The overall timeline averages just over 30 days, though some candidates complete the process in as little as three weeks, while others, especially for senior roles, may take up to eight weeks.

Common OpenAI Software Engineer Interview Questions

The questions you encounter at OpenAI will challenge both your technical expertise and your ability to think critically about complex systems. To some degree all interview questions are practical and usually the questions asked are language agnostic. 

Coding Questions 

The coding round at OpenAI is more practical than at most other companies. There will be algorithmic questions, but they’l cover topic you’d also cover during work. Your code has to be fast and flexible, with a focus on scalability and the possibility to adapt in the future. 

Problems often relate to trees, binary search, graphs and recursion.

Examples of common topics at OpenAI are: 

• Time-based data structures
• Versioned data stores
• Coroutines in your chosen language  such as multithreading and concurrency
• Object-oriented programming concepts such as iterator classes and inheritance

Preparation Tip: Aim to write clean, well-structured code and analyze time complexity.

System Design Questions 

The system design interview often focuses on scalability and depth of knowledge. You might be asked to design a chatbot service capable of handling over a million concurrent requests or a notification system. Interviewers will expect you to discuss trade-offs in load balancing, caching strategies, and failover mechanisms, while also considering latency requirements and cost efficiency. Expect a lot of follow-up questions. 

OpenAI prepares candidates well for their interviews so keep an eye out for any tips they give you.

Problems presented often relate to APIsm consistent hashing, load balancing, cashing and cloud architecture. 

Examples of common questions at OpenAI are: 

• Design a chatbot service that can handle over 1 million concurrent requests with minimal latency
• Design a platform like Twitter

Preparation Tip: Design challenges often reflect AI-centric infrastructure.

Behavioral Questions

Behavioral interviews use open-ended but standard questions to understand how you collaborate, adapt, and solve problems under ambiguity, and to learn more about your background. Questions like “Tell me about a time you solved an ambiguous problem” allow you to demonstrate both your problem-solving skills and your alignment with OpenAI’s culture. The STAR method can help you answer in a clear and impactful way.

OpenAI recommends to read their blog to brush up your knowledge about topics you find interesting. Don’t skip articles discussion ethics and safety in AI! 

Another important topic covered in the behavioral interviews is working with teams. Expect questions about the following topics: 

• Times you’ve experienced conflict between teams
• Times you’ve had to work with multiple teams on one product 
• Competing ideas on how to move a project forward within your own team. 

Preparation Tip: Showcase curiosity and ownership, two traits OpenAI values highly.

Mistakes to Avoid During OpenAI Interviews

Even strong candidates can make avoidable mistakes. Here are some common ones to look out for:

Over-preparing on LeetCode, Neglecting Design & Collaboration

One of the most common mistakes candidates make is focusing almost exclusively on Leetcode-style algorithm practice while neglecting system design and collaboration skills. While strong algorithmic ability is important, OpenAI engineers work on large-scale, complex systems that require architectural thinking and cross-team communication.

Poor Communication During Coding

Another frequent mistake is failing to communicate during live coding sessions. Silent coding can make it difficult for interviewers to follow your reasoning, which may lead to a lower evaluation even if your solution is correct.

Lack of AI/ML Domain Awareness

Candidates without any AI or ML background sometimes underestimate the importance of understanding core concepts. While you do not need to know every detail of transformer architecture, having a working knowledge of basic AI principles can set you apart.

Underestimating Behavioral Rounds

Finally, some candidates approach behavioral interviews as an afterthought. At OpenAI, these rounds are critical for assessing mission alignment and collaboration potential. There have been cases where technically strong candidates failed to progress because they gave minimal answers during behavioral questions.

What Happens After the OpenAI Interview?

Once your interviews are complete, most candidates hear back within one to two weeks. However, delays can happen, especially if key stakeholders are unavailable or if you are in a “hold” pool while the team evaluates other candidates. 

Your recruiter may ask for references during the decision stage. 

If you receive an offer, it will typically include a highly competitive base salary, generous equity, and occasionally performance-based bonuses. In some cases, top talent is also eligible for special retention bonuses like the ones awarded in 2025.

If you are not selected, you are generally welcome to reapply after six to twelve months. This gap allows you to build additional experience and address any areas where you may have underperformed.

Frequently Asked Questions

How many rounds are in the OpenAI SWE interview?

Most candidates complete between four and six rounds, including the recruiter call, technical phone screen, and multiple onsite interviews.

How long does the process take?

The average is just over 30 days, though some finish in three weeks and others take up to eight weeks.

What programming languages should I know?

Python is common, but knowledge of C++, Go, or Rust can be advantageous for certain teams.

Do I need prior AI/ML experience?

Not necessarily, but showing interest in the field and willingness to learn is highly valued.

How is the system design round different at OpenAI?

It often includes considerations for serving machine learning models and handling distributed compute workloads.

Does OpenAI use whiteboard interviews?

Most technical interviews are now conducted on collaborative coding platforms rather than whiteboards.

Can I reapply if rejected?

Yes, typically after a six to twelve month waiting period.

Conclusion

The OpenAI software engineer interview process is demanding because the company is looking for more than just technical skill. OpenAI looks for engineers who can solve complex problems, work effectively in collaborative environments, and stay aligned with its mission to ensure artificial intelligence benefits all of humanity.

By preparing across coding, system design, and behavioral dimensions, and by demonstrating curiosity and adaptability, you can significantly improve your chances of success.

If you want to refine your preparation further, explore the other interview guides and technical practice resources available on the our blog.