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OpenAI L4 (Senior) Software Engineer Interview Guide
A comprehensive guide to the OpenAI L4 interview process
The OpenAI senior software engineer interview process starts with a recruiter screen, followed by two technical screens (one coding, one system design), then moves to a final onsite loop with 4 rounds covering coding, system design, behavioral questions, and a technical project presentation. The entire process typically takes 6-8 weeks from start to finish, though it can stretch to 3+ months due to scheduling delays and internal coordination bottlenecks that some candidates report.
Senior candidates get evaluated hard across multiple areas. The system design rounds and project presentation carry the most weight for level determination, since they directly assess your ability to architect complex systems and communicate technical decisions at a senior level. The behavioral interviews also matter significantly because they evaluate your alignment with OpenAI's mission around AI safety and responsible development. Unlike junior roles where you might skip the project presentation entirely, senior candidates must demonstrate leadership through concrete examples of guiding technical decisions and mentoring teammates. The coding rounds expect you to write production-quality code that's not just correct but also maintainable and scalable, reflecting the higher standards expected at the senior level.
"They expect most people to downlevel coming in, regardless of what company you're from"
— Recent OpenAI Senior candidate
The interview consists of 6 total rounds:
- Recruiter Intro Call
- Coding Screen
- System Design Screen
- Onsite (Usually virtual)
- Coding Round
- System Design Round
- Technical Project Presentation
- Behavioral Interview
Interview Rounds
Recruiter Intro Call
Your first conversation is a straightforward 30-minute call with your recruiter. This isn't technical, it's more like mutual exploration to see if there's a good fit before you both invest time in the harder rounds.
The conversation flows through your background, covering career highlights and how your experience connects to what they need. You'll definitely get asked why you want to work at OpenAI specifically, so skip the generic "cool AI company" answers. They want to understand your real motivation and whether you've actually thought about their mission around building safe AGI.
This round carries more weight than you'd expect for an initial screen. They care a lot about mission alignment because they're trying to figure out if you actually understand and care about responsible AI development. How you communicate matters too, since they need people who can explain complex ideas clearly when you're working on cutting-edge AI systems.
The person you're talking to will also outline the rest of the process and answer any big-picture questions about the role or team. This is your chance to understand what comes next: the coding screen followed by the system design screen, then the onsite rounds.
Come with good questions about team dynamics, the specific projects you'd work on, or how OpenAI tackles the technical challenges you care about. The goal is having a real conversation about mutual fit, not just checking boxes.
"Having a good rapport with my recruiter was also very helpful as far as interview prep - we had a few phone calls where they helped lay out what interviewers would be looking for in the next round/s and hints on how to best prep"
— Recent OpenAI Senior candidate
Coding Screen
After that first call, you'll hit the first technical round: a 60-minute live coding session that sets the tone for everything else. This usually happens over CoderPad, though some candidates get a HackerRank-style thing instead. Either way, you're writing code while an interviewer watches and asks questions in real time.
The problems feel more practical than typical LeetCode grinding. You'll get questions about time-indexed data handling, implementing iterators with state, or building simple caching mechanisms. The concurrency and OOP design elements make this different from pure algorithmic puzzles. They want to see how you think about real software problems that could actually come up at OpenAI.
Most sessions have 1-2 problems, and the interviewer will watch your pace to decide whether to go deeper on one complex challenge or move through multiple scenarios. You can pick any programming language you're comfortable with, which is nice flexibility that not every company gives you.
"I think the main challenge in my experience was the amount of code you had to output in the 1 hour session. Even when it went well and I did outline a specific / clear approach from the start I was typing the whole time and finished passing all the test cases just in time. So I would say index on getting something working quickly since there isn't some algorithmic insight you need for any of the questions, usually just a lot of functionality and test cases"
— Recent OpenAI Senior candidate
You're evaluated on four main aspects:
- Problem-solving & coding skills: How you break down the problem and implement a working solution
- Code quality & maintainability: Clean, readable code that looks like it could go into production
- Speed & correctness under pressure: Reasonable pace while handling edge cases within the time limit
- Communication & approach clarity: Explaining your thought process and responding well to hints
The no-reference policy means you're coding from memory, so brush up on your language's standard library and common patterns beforehand. Testing your solutions thoroughly matters. Interviewers like when you walk through edge cases or explain how you'd validate the code works.
Live, up-to-date
Most commonly asked Coding questions
OpenAI
Senior
System Design Screen
The format is designing a complete software system from scratch using a shared online whiteboard. You might be asked to architect something like a simplified Twitter feed, real-time notification system, or ML model serving platform. These problems mirror the large-scale challenges OpenAI faces internally. The interviewer will guide you through it, probing deeper into your architectural decisions and asking follow-up questions about scalability, reliability, and trade-offs.
As a senior candidate, you need to operate at multiple levels of abstraction at once. Start with high-level system components and data flow, then drill down into specific technology choices when asked. The interviewer will test your technical depth by exploring why you chose PostgreSQL over MongoDB, how you'd handle a 10x traffic spike, or what happens when your primary data center goes offline.
You're evaluated on four main things: system architecture design and technical depth carry the most weight, since they directly test your ability to build scalable systems and show deep understanding of the technologies involved. Trade-off reasoning and communication clarity round out the evaluation, focusing on your ability to justify decisions and explain complex concepts clearly.
The interactive nature means you'll be refining your design based on the interviewer's questions and new requirements. They might introduce new constraints midway through or ask you to optimize for a different metric, testing your ability to adapt your architecture thoughtfully rather than just defend your first approach.
Live, up-to-date
Most commonly asked System Design questions
OpenAI
Senior
Onsite
Coding
The format is effectively the same as your earlier technical coding screen, just with different problems.
You can choose to work in your own IDE with screen sharing, which most senior candidates prefer since it lets you use your familiar environment and shortcuts. The alternative is using CoderPad, but given how advanced these problems are, having access to your normal development setup often makes the difference between a smooth experience and struggling with an unfamiliar interface.
"I've heard that they also won't pass you if you have a 2/4 or low 3/4 on coding even if you ace everything else; they really want people who can be productive building / writing code, not just arch / design / org alignment"
— Recent OpenAI Senior candidate
You're evaluated on four main things: problem-solving and algorithms carry the highest weight, since they test your ability to tackle complex programming challenges with appropriate data structures and efficient approaches. Code quality and scalability matter equally, reflecting the senior-level expectation that your solutions should be production-ready rather than just functionally correct. Testing and thoroughness round out the evaluation, focusing on your attention to edge cases and ability to reason through correctness, while communication tests how well you explain your approach and respond to interviewer feedback.
The interviewer will probably introduce additional constraints or ask for optimizations after you complete the initial solution, so don't spend all your time perfecting the first implementation. This iterative aspect mirrors real-world development where requirements evolve, and they want to see how you handle changing specifications while maintaining code quality.
Live, up-to-date
Most commonly asked Coding questions
OpenAI
Senior
System Design
The system design round during your final interview loop is the most technically challenging conversation you'll have throughout the entire process, and it carries enormous weight in determining whether you get an offer at the senior level. Again, the format mirrors your earlier system design screen, but you'll get a different problem and face deeper technical questioning.
The interactive nature means you're constantly adapting your design based on the interviewer's probing questions and evolving requirements. They'll start by asking you to sketch the high-level architecture, then drill down into specific components when they want to test your technical depth. Expect questions like "How would you handle a 10x traffic spike during a product launch?" or "What happens if your primary data center goes offline for six hours?" The interviewer wants to see you think through failure scenarios and show that you understand the operational complexities of running distributed systems in production.
"I do remember the deep dives going both wide and deep - in one discussion for a notif system I said we could colocate TCP connections for all subscribers to a particular topic and we ended up talking about concurrency bottlenecks at the level of allocating file descriptors; we also talked about global replication, consistent hashing for load distribution/failover, handling bursty traffic in memory vs in a log based queue"
— Recent OpenAI Senior candidate
You're evaluated on four main things: scalable system architecture and technical breadth carry the highest weight, since they directly test your ability to design systems that can handle OpenAI's scale while showing deep understanding of the underlying technologies. Trade-off analysis and interactive problem-solving round out the evaluation, focusing on your ability to make informed decisions about competing approaches and collaborate effectively during the design process.
The key to success here is balancing high-level architectural thinking with the ability to dive deep into implementation details when pressed. You need to show you can reason about load balancers, database sharding strategies, caching layers, and message queues, but also step back and explain how all these pieces work together to solve the business problem. The interviewer will probably introduce new constraints or requirements midway through, testing your ability to evolve your design gracefully rather than starting from scratch.
Live, up-to-date
Most commonly asked System Design questions
OpenAI
Senior
Behavioral
This is typically a 30-minute conversation.
The interviewer will probably be someone from the engineering team you'd be joining, and they're trying to answer a specific question: would you thrive in OpenAI's highly collaborative, fast-moving environment where engineers regularly work across disciplines with researchers, product managers, and safety teams? The questions feel more like a structured conversation than an interrogation, but don't mistake the informal tone for low stakes because this round carries real weight in the hiring decision.
You'll get scenarios that dig into your experience with cross-functional collaboration, like times you had to work with teams that had different priorities or technical perspectives than your own. They want to understand how you navigate the inevitable friction that comes up when multiple teams are trying to ship complex AI products under tight timelines. Expect follow-up questions that probe deeper into your specific actions and the ultimate outcomes of challenging situations.
You're evaluated on three main things: teamwork and collaboration carries the highest weight, since they need evidence you can work effectively with diverse teams and contribute to collective success rather than just individual achievement. Conflict resolution and adaptability round out the evaluation, focusing on your ability to navigate disagreements constructively and stay effective when circumstances change rapidly.
The most successful candidates come prepared with concrete examples of times they've worked with non-engineering teams or handled situations where initial approaches didn't work out. OpenAI operates in pretty uncharted territory, so they're looking for people who can stay collaborative and supportive when facing ambiguity or shifting priorities.
Technical Project Presentation
The technical project presentation is your chance to show off the depth of your engineering experience through a detailed retrospective of your most impactful work. It's a 45-minute interview where you will present on a past project.
Unlike the live coding or system design rounds where you're solving new problems on the spot, this presentation lets you shine by diving deep into a project you know inside and out. You'll join a video call and share your screen to walk through slides covering the problem you solved, your technical approach, the challenges you hit, and the ultimate impact of your work. The interviewer will ask clarifying questions throughout, probing into your decision-making process and technical reasoning.
Picking the right project is crucial for success here. Choose something where you played a big role in both the technical design and implementation, ideally a project that took several months and involved real technical challenges. The best presentations tell a compelling story that shows multiple aspects of senior engineering: architecture decisions, collaboration with stakeholders, handling uncertainty, and measuring success through concrete metrics.
"It's important to emphasize how past projects relate if you're in a team specific vs general pipeline. Since OpenAI and Anthropic basically have first pick on the whole industry right now, they can select for someone who's worked on the exact type of project / system that they're hiring for"
— Recent OpenAI Senior candidate
You're evaluated on four main things: technical expertise and communication clarity carry the highest weight, since they directly test your ability to understand complex systems and explain them to others at a senior level. Impact and results matter for showing that you can connect technical work to business outcomes, while decision-making insight shows your ability to navigate trade-offs and choose appropriate solutions given constraints.
The interactive nature means you should prepare for deep technical questions about your architecture choices, alternative approaches you considered, and how you might handle different requirements or scale constraints. The interviewer wants to understand not just what you built, but why you built it that way and what you learned from it.
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