OpenAI Software Engineer (New Grad) Interview

OpenAI's New Grad Software Engineer (SWE) interview combines practical coding challenges that test your understanding of object-oriented programming with a behavioral conversation built around OpenAI's mission. Each stage tests a different dimension: how you think, how you build, and your approach to AI.

This guide breaks down each stage of the New Grad SWE interview process, what OpenAI interviewers look for, and how to prepare with example questions, actionable tips, and resources.

OpenAI New Grad SWE interview process

The OpenAI New Grad SWE interview loop typically runs 4-5 stages, with team matching deferred until after the offer.

Here's what the interview process can look like:

1. Recruiter screen: A brief conversation about your experience and interest in OpenAI
2. Online assessment: A timed coding assessment on HackerRank or a similar platform
3. First-round coding interview: A virtual coding interview focused on a single algorithmic challenge
4. Final-round coding interview: An object-oriented design build, extended iteratively as the interviewer adds requirements
5. Final-round behavioral interview: A conversational round covering your background, motivation for OpenAI, and perspective on AI safety

You won't meet a hiring manager during the loop itself, but OpenAI's recruiters are hands-on. They're available to answer questions throughout the process and will provide information about the coding challenges to help you prepare.

Recruiter screen

The OpenAI New Grad SWE recruiter screen is a 15-20 minute conversation covering your interest in the role, your past projects, and scheduling logistics for follow-up rounds. Some candidates skip this stage entirely and move directly to the online assessment, though that's uncommon.

Expect high-level questions about projects you worked on as a student or intern. The call is short, so detailed technical depth isn't the goal. Recruiters will also confirm your preferred coding language for subsequent rounds if you want to use something other than Python.

Recruiters look for:

• Genuine interest in OpenAI: Whether your motivation reads as authentic and OpenAI-specific in a brief conversation
• Communication clarity: How concisely you can summarize your background and past projects
• Logistical fit: Confirmation of timeline, location, work authorization, and language preferences
• Cultural alignment signals: Early read on how you think about AI and OpenAI's role in shaping it

Sample questions

Here are some real interview questions reported by candidates:

• Why do you want to work at OpenAI?
• What parts of OpenAI's mission statement resonate with you?

Online assessment

OpenAI's New Grad SWE online assessment is a timed coding test, typically administered through HackerRank or a similar platform. Expect a multi-part challenge that escalates in difficulty across two stages: an initial algorithmic task, then an extension that adds complexity on top of your first solution.

The online assessment is automated, so prioritize correctness on test cases over elegant code. Recruiters move responsive candidates forward quickly, sometimes advancing strong submissions within days.

Interviewers evaluate:

• Correctness: Whether your solution passes the full set of test cases, including edge cases
• Pattern recognition: How quickly you identify the underlying algorithmic pattern and apply it
• Extension handling: Whether your initial approach holds up when the second part of the problem adds complexity
• Time management: How efficiently you work through both parts within the time limit

Sample questions

Here are examples of what the online assessment can look like:

• Build a hash tree algorithm.

First-round coding interview

The OpenAI New Grad SWE first-round coding interview is a virtual session built around a single coding challenge, scored on correctness and clean implementation rather than runtime efficiency. Interviewers may state explicitly that they care less about how fast your solution runs and more about whether the code does what it's supposed to do.

The session runs on a CoderPad-style environment, and language preferences shared with the recruiter ahead of time will be reflected in the setup. Expect a brief intro before the interviewer drops directly into the problem; broader resume and team conversation tends to come at the end if there's time.

Interviewers look for:

• Correctness: Whether your solution produces the intended output across standard and edge-case inputs
• Code clarity: How readable and well-structured your implementation is
• Reasoning: Your ability to explain what you're doing and why as you work through the problem
• Language fluency: Comfort writing idiomatic code in your chosen language without leaning on the interviewer for syntax
• Follow-up handling: How you respond when the interviewer presses on edge cases, alternative approaches, or trade-offs

Recently asked questions

Here are some real interview questions reported by candidates:

• Clone a linked list with a random pointer.

Final-round coding interview

The final-round coding interview for OpenAI New Grad SWEs is an iterative object-oriented design challenge. Interviewers may push directly into a system you build function by function, adding new methods as the session unfolds.

Interviewers look for:

• Class design: Whether your initial structure is clean, extensible, and uses inheritance and composition appropriately
• State management: How you track and update state across multiple methods and interactions
• Iterative extension: Your ability to absorb new requirements mid-session without rewriting the foundation
• Data structure choices: Whether the structures you pick (dictionaries, sets, queues, counters) fit how the system will be used
• OOP fundamentals: Comfort with classes, inheritance, polymorphism, and encapsulation as design tools, not just syntax

Recently asked questions

Here are some real interview questions reported by candidates:

• Design an algorithm to find times when multiple people are available.
• Design a customer support chatbot.

Final-round behavioral interview

The OpenAI New Grad SWE behavioral interview covers your motivation for OpenAI specifically, your perspective on AI, and the depth of your past work. Interviewers may share their own views on alignment and regulation and invite you to push back.

The session typically opens with a quick intro and a walk through the most memorable item on your resume, then moves into questions about your interest in the company that can segue directly into an open discussion about OpenAI's mission.

Interviewers look for:

• Mission alignment: How clearly you can articulate why OpenAI specifically, beyond general interest in AI
• Perspective on AI safety: Whether you've formed a considered view on alignment, regulation, and the trajectory of AI development
• Resume depth: Your ability to walk through past work with technical specificity and reflection on impact
• Open-ended discussion: Comfort moving fluidly between structured questions and substantive back-and-forth on hard topics
• Conflict navigation: How you handle disagreement, anchored in real examples from past roles or projects

Recently asked questions

Here are recent questions reported by candidates:

• Tell me about the most memorable or impactful project on your resume.
• What are the challenges in ensuring generative AI doesn’t produce harmful or unsafe content, and how would you address them?
• You have a new capability that's extremely powerful but potentially risky. How do you decide whether or not to ship it?

How to prepare for the OpenAI New Grad SWE interview

1. Practice pattern-based coding for the early rounds: The online assessment and first-round coding interview skew algorithmic. Work through patterns like greedy, two-pointer, and sliding window; the assessment's two-part structure tests how quickly you can recognize a pattern and extend it when complexity gets layered on top.
2. Build OOP fluency for the final coding round: Practice designing systems that grow over the session, focusing on clean class structure, state management, and choosing data structures that support new requirements as they drop in. Mock the live-extension format with a partner who can add new methods mid-session; the round's difficulty lies in absorbing changes once the session is already running.
3. Prioritize correctness over runtime: Interviewers may explicitly tell you they care more about your solution producing the right output than about how fast it runs. Use the time you save by not over-optimizing to handle edge cases, write readable code, and explain your reasoning.
4. Develop a considered view on AI: Behavioral interviewers may share their own stance on alignment and regulation and ask for yours. Read enough on alignment, capability research, and the AI policy landscape to hold a real conversation, and review common OpenAI SWE interview questions to see what AI-specific framings come up.
5. Anchor "why OpenAI" in mission: This question can segue directly into a discussion about the company's direction. Tie your answer to OpenAI's mission and your own perspective on where AI is heading, without anchoring on specific products or research outputs.
6. Practice with mock interviews: Run through coding rounds with someone who can mimic an interviewer adding new requirements mid-session. The final-round coding format is particularly hard to prepare for solo because the difficulty is in adapting to live changes.

About the OpenAI New Grad SWE role

OpenAI New Grad SWEs contribute hands-on across technical domains like safety, model training, and infrastructure, with the specific scope shaped by the team you join. The role emphasizes fast learning, autonomy, and direct collaboration with a senior engineering team.

OpenAI New Grad SWEs are typically expected to:

• Write and ship code in a fast-paced environment: OpenAI runs at startup speed with high standards for output and ambition.
• Pursue learning opportunities independently: The team and individual autonomy at OpenAI gives new grads room to experiment with the topics and disciplines that interest them.
• Adapt to shifting priorities and goals: OpenAI's roadmap evolves quickly, and team members are expected to absorb frequent changes without losing momentum.
• Collaborate with and learn from a senior team: OpenAI's engineers are among the most experienced in AI; new grads are expected to ask questions, take feedback, and grow quickly.

Additional resources

• OpenAI interview process
• OpenAI Software Engineer interview guide
• OpenAI Full-Stack Engineer interview guide
• OpenAI Research Engineer interview guide
• Anthropic Software Engineer interview guide
• Tech interview process overview

FAQs about the OpenAI New Grad SWE interview

How long is the OpenAI New Grad SWE interview process?

The OpenAI New Grad SWE interview process typically runs between 2-8 weeks, with most of the variability coming from scheduling rather than evaluation cycles. Recruiters move responsive candidates forward quickly between stages, but interview availability can stretch out by weeks during peak periods.

Does OpenAI's New Grad SWE interview loop include a system design round?

OpenAI's New Grad SWE interviews may not include a dedicated system design round based on recent candidate experiences. The final-round coding interview is sometimes closer to an object-oriented design challenge than a traditional system design conversation, and tests how you structure code rather than how you architect distributed systems. This may vary by team or hiring track.

What programming languages can you use in the OpenAI SWE coding interviews?

You can request a non-default language for the OpenAI SWE coding interviews by noting it in your meeting invite reply or with your recruiter ahead of time. Python is the default in most session setups, but candidates can request alternatives like C++, Java, or Go. Communicate the preference early so the environment is configured correctly before the round starts.

Does OpenAI have a culture fit assessment for New Grad SWEs?

OpenAI doesn't run a dedicated culture fit assessment as a standalone round in the New Grad SWE interview loop. The closest equivalent is the final-round behavioral interview, which combines resume depth, motivation for OpenAI specifically, and an open conversation about AI safety and the company's mission.

How much does an OpenAI New Grad Software Engineer make?

Here are the reported compensation ranges by level for OpenAI New Grad Software Engineers, according to Levels.fyi:

• L2 (Entry Level): ~$249K
• L3 (Software Engineer): ~$337K

Total compensation is split between base salary, equity grants, and bonus. For L2, that's roughly $168K base, $80K annual stock, and a small bonus component.