Top 20 OpenAI Product Manager Interview Questions & Interview Process Tips

Thinking of applying for a product manager role with OpenAI? Join us as we explore the interview process and the top 20 questions you’re likely to face.

OpenAI is one of the most sought-after companies to work for, offering competitive salaries, generous benefits, and the chance to work on groundbreaking AI technologies. PMs at OpenAI lead the development of cutting-edge AI products, working alongside world-class engineers, researchers, and designers.

A Product Manager's salary at OpenAI can range between $700,000 and $1m, including base salary, performance bonuses, and stock options—making it one of the highest-paying PM roles in the industry. However, this prestige comes with intense competition, as only the top 1% of applicants typically secure a position.

With OpenAI's rapid expansion and continued investment in AI, the demand for top-tier Product Managers has never been higher. To stand out, you need to be exceptionally prepared, and master technical, strategic, and behavioral aspects of the interview process.

Based on insights from Dr Nancy Li - who’s helped over 1500 product managers land high-paying product manager jobs in MAANG companies and unicorn startups - this guide walks you through every stage of the OpenAI PM interview process, covering the 20 most commonly asked questions, provides expert-backed strategies, and equips you with the tools needed to succeed.

OpenAI PM Interview Process: Step-by-Step Breakdown

If you’re serious about landing that OpenAI product manager (PM) role you’ve got your eye on, you’ll need to navigate a multi-stage interview process. Each one is designed to assess both your experience and skill set,  including product design, product execution, analytics, product thought leadership, technical AI knowledge, and case studies. Let’s break down that process to help you understand how to prepare to kill it at every point.

Round #1 - Application & Initial Recruiter Screen (Phone Call)

After making your application to your intended OpenAI PM role, the first person you’ll usually hear from is a talent recruiter or recruiting coordinator. This will typically be over the phone or via a Zoom call. This part serves as a high-level screening to assess your background, motivations, and overall fit before moving forward in the interview process.

This call should last between 30-45 minutes, during which you’re likely to get asked general questions about you personally, including:

1. “Tell me about yourself and your background.”
2. “Why do you want to work at OpenAI?”
3. “What is your experience working with AI-driven products?”
4. “How do you approach problem-solving as a PM?”
5. “What’s your experience working cross-functionally with engineers and designers?”

How to Prepare

In order to make your mark during this screening interview, you should research OpenAI’s mission, as well as their current ongoing projects. Also, when you get asked the “Tell me about yourself” question, use the PAST-PRESENT-FUTURE structure. 

For example, you might say:

“I started in product management at a SaaS startup, focusing on user engagement (Past). Now, as a Senior PM in AI, I lead ML-driven product development (Present). I'm eager to apply my experience at OpenAI to build impactful AI products (Future).”

This structure keeps your answer clear and engaging, making sure you hit the key points without rambling - something we can all do from time to time.

Round #2 - First-Round Hiring Manager Interview (Behavioral Questions – 45 Minutes, Zoom)

If you successfully get through the recruiter screen, you’ll then move on to an interview with the first-round hiring manager - again via Zoom. This stage lasts around 45 minutes and kicks off the first of the top 20 behavioral questions you’ll need to master for the OpenAI interview.

As such, you’ll typically get asked things like:

      6. “Describe a situation where you had to advocate for change within your organization. What challenges did you face, and how did you overcome them?”
      7. “Can you provide an example of a time when you made a trade-off between user experience and technical feasibility?”

How to Prepare

When answering these behavioral questions, it’s best to use the GRAIL system. What’s that? Well, it offers a structured approach that ensures your responses are concise, logical and have an impact. This is what each letter stands for:

• G - Get to the Point → Start with a direct and concise answer to the question. Avoid unnecessary context or buildup.
• R - Reason & Why → Explain the reasoning behind your actions and why the situation required your approach.
• A - Actions → Clearly outline the specific steps you took to address the challenge or problem.
• I - Impact → Highlight the measurable results or outcomes of your actions, using data if possible.
• L - Learning → Reflect on key takeaways and how the experience shaped your approach to similar challenges in the future.

For example, when answering question #6 “Describe a situation where you had to advocate for change within your organization. What challenges did you face, and how did you overcome them?”, you’d approach it in the following way using the GRAIL system:

G: I pushed for a simpler onboarding process because too many users were dropping off.

R: We had a 30% drop-off rate, which was hurting activation and revenue, so I knew something had to change. 

A: I gathered feedback, proposed a redesign, and worked with engineers to streamline the process. 

I: After launching the changes, drop-offs decreased by 20%, and retention improved.

L: This showed me how data-driven advocacy and collaboration can drive real impact.”

Nailing this round shows you can solve problems, lead effectively, and fit right in at OpenAI. To go more in-depth into behavioral questions, check out this Video on the subject that takes you through everything you need to know.

Round #3. Second-Round Hiring Manager Interview Part 1 (Product Design – 30 Minutes, Zoom)

If successful in round 2, you’ll move on to the next step, which focuses on product thinking, problem-solving, and structuring a user-first design approach while looking at how you tackle AI-related design challenges.

Questions that arise might take this form:

      8. “Design a solution to communicate with pets using AI”
      9. “Design the future of music platform”

 How to Prepare

Here you should be applying frameworks like MODIFIED CIRCLES (Context, Users, Needs, Solutions, Prioritization, MVP) so that you can clearly show an ability to think critically about AI-specific challenges.

For instance, in answer to question #8 “Design a solution to communicate with pets using AI”, a good answer would look something like this:

“Pet owners often struggle to understand their pets (Context), which leads to frustration and missed health cues. Since the main users would be pet owners, vets, and trainers (Users), the key need is a way to interpret vocalizations and body language in real-time (Needs). 

One solution could be an AI-powered smart collar that analyzes sounds and movements to translate emotions like hunger or stress (Solutions). I’d prioritize real-time emotion detection and simple alerts before expanding to predictive health tracking (Prioritization). 

For an MVP, I’d launch a basic app that sends owners notifications about their pet’s mood, helping them respond more effectively (MVP)”

Round #3. Second-Round Hiring Manager Interview Part 2 (Product Metrics – 30 Minutes, Zoom)

Whether the second part of round two - Product Metrics - is conducted with Part 1 or separately will depend on the role you’re applying for. Either way, however, it should last 30, again be conducted on Zoom and include questions like:

      10. “How would you measure success for OpenAI? What if instrumentation went down?”
      11. “What metrics would you use to measure the success of a product feature you've implemented?”

How to Prepare

Dr Li’s proprietary MYCSPHD (North Star Metrics, Product Health Metrics) framework offers candidates the very best chance of shining at this point of the interview process. The framework helps you t show that you can define the right success metrics, track product health, and make data-driven decisions that align with OpenAI’s goals. 

As such, a solid answer to the question: OpenAI’s success metrics might look like this when using the MYCSPHD framework:

• "OpenAI’s success comes down to how well it advances AI in a way that benefits people (M). A key sign of impact is how widely businesses and developers adopt its models (Y). Different users have different needs, so tracking success across startups, enterprises, and researchers matters (C). 

I’d measure retention, engagement, and model accuracy while ensuring uptime and reliability (S&P). If tracking failed, I’d use proxy data and customer feedback (H), and to prevent future failures, I’d build in backup tracking systems (D)."

Using this approach proves you know how to prioritize what really matters, adapt when data is missing, and think critically about measuring AI products—just like a strong PM should.

Round #4. Technical & Analytical Assessment (60 Minutes, Zoom)

If you’ve reached this point, well done! Many don’t. However, there’s still a lot of work to do. Next, you’ll face a 60-minute Zoom call, most likely with a senior product manager, data scientist or engineer. 

Here, you’ll be tested on your analytical thinking, AI-specific knowledge, and technical feasibility of product decisions. It’s designed to assess how well you break down complex problems, work with data, and make informed technical trade-offs.

Common questions that get asked include:

      12. “What are the key considerations when integrating a machine learning model into a consumer-facing product?”
      13. “Can you explain the concept of A/B testing and how it applies to product development?”

How to Prepare

Succeeding in this round is all about showing you can think like a data-driven PM. To prepare, make sure you can explain how you make decisions using data, even when it’s incomplete. As such, be ready to discuss model reliability, performance trade-offs, and ethical considerations, especially in the context of AI-driven products. 

You should also feel comfortable walking through A/B testing methodologies, why statistical significance matters, and how you'd use experiments to improve product outcomes. This is your chance to prove that you don’t just understand product metrics—you know how to apply them strategically to drive impact.

Here’s how you could answer Question #12 “What are the key considerations when integrating a machine learning model into a consumer-facing product?” if asked…

"The biggest challenge is making sure the model is accurate, fast, and reliable in real-world scenarios. If it's too slow or inconsistent, users will drop off, so balancing performance trade-offs is key. 

Ethical concerns, like bias and transparency, also matter because a model that’s unfair or unexplainable can break user trust. I'd use A/B testing to measure real impact and make sure any changes are statistically significant. 

Since data is never perfect, I'd take an iterative approach—monitoring results, learning from gaps, and improving the model over time."

Round #5. On-Site Interviews (Back-to-Back Interviews, 45 Minutes Each)

At this stage, it starts getting even more intense, so you need to be prepared. Round five will usually involve visiting OpenAI’s offices, where you’ll be faced with multiple, back-to-back interviews with the company’s PMs, engineers and leaders. 

Here you’ll need to answer deep-dive interviews covering strategy, vision, and execution, meaning you could be asked…:

      14. “How do you envision the future of AI impacting product development in the next five years?”
      15. “How would you prioritize feature requests from various stakeholders, including customers, sales, and engineering teams?”

How to Prepare

To stand out from the crowd in this round, you’ll need to show a strong grasp of AI trends, regulations, and ethics. You should be ready to discuss how emerging AI advancements impact product decisions and what challenges come with regulatory compliance. 

Demonstrating your ability to mitigate bias and ensure fairness in AI deployment will be crucial. Lastly, make sure you apply Dr Li’s GUCCI framework (Growth, Unmet Needs, Customer Impact, Competition, Integrated Ecosystem) to structure your product strategy—this will help showcase your ability to think critically and align AI-driven products with business goals. 

If you were to answer Question #15 “How would you prioritize feature requests from various stakeholders, including customers, sales, and engineering teams?” using this approach, a good answer would look something like this:

"I’d prioritize feature requests by making sure they align with what matters most for users and the business. I’d consider Growth Potential—will this drive adoption? Unmet needs—does it solve an immediate pain point? Customer impact—how many users benefit? Competition—are we falling behind industry trends? 

And Integrated Ecosystem—do we have the resources to build it? Customer feedback is key, but I’d also check with sales on market demand and engineering on feasibility. If a request drives AI adoption or addresses a regulatory challenge, it moves up the list. In the end, it’s about balancing quick wins with long-term impact."

Round #6. Cultural Fit & Leadership Interviews (45 Minutes Each, Zoom or In-Person)

Next, you’ll go through a series of interviews that dive into mission alignment, leadership, and teamwork. These are usually led by senior leaders, execs, or cross-functional partners and can happen over Zoom or in person at OpenAI’s offices. Unlike earlier rounds, these are often scheduled on a different day so there’s more time for deeper conversations. 

You’ll be tested on how well you fit OpenAI’s values, how you lead and collaborate, and how you handle tough challenges—both in your role and across the company.

Common questions in this section include:

      16. “How do you align your work with the mission and values of OpenAI?”
      17. “Can you provide an example of a time when you led a cross-functional team to achieve a product goal?”

How to Prepare

The key to this round is showing that you don’t just want to work at OpenAI, rather you’re the right fit for its mission and culture. That’s why you should be ready to connect your past experiences to OpenAI’s goals and explain how your work has made a real impact. 

You’ll also need to show that you collaborate well, adapt to change, and thrive in uncertain situations. Expect questions that test how you handle ambiguity, make tough decisions, and lead in complex environments.

A great way to answer Question #16 “How do you align your work with the mission and values of OpenAI?” would be something like…

"OpenAI’s mission really resonates with me because I’ve always looked for ways to build AI products that create real impact. In past roles, I’ve worked with engineers and researchers to solve complex problems while balancing ethical considerations. 

I’m comfortable in fast-moving environments where things change quickly, and I know how to adapt while staying focused on the bigger picture. That’s why OpenAI feels like the right fit—not just as a company, but as a mission I can contribute to in a meaningful way."

Round #7. Final Round: Case Study or Presentation (Virtual or In-Person)

If you’ve reached the last round, you should pat yourself on the back, as you’re obviously doing a lot of things right. That said, the challenge is not over, yet.

At this stage, you’ll likely be asked to present a case study or analyze an OpenAI product in depth to test your strategic thinking, problem-solving, and ability to communicate complex ideas.

Although not technically questions, you’ll be asked to do something like…

      18. “Analyze a current OpenAI product and propose three improvements to enhance user engagement.”

How to Prepare

The key here is to keep your thinking structured and your recommendations backed by logic and data. Break problems down step by step so it’s easy to follow your thought process, and use examples or data to support your points. 

Since this is OpenAI, be ready to talk about real challenges in AI, like model limitations, ethical concerns, or how to get people to trust and use AI products. Most importantly, focus on communicating clearly—it’s not just about having a great idea, but showing how you think and adapt.

Your case study could have this kind of focus:

"I’d choose ChatGPT because it’s OpenAI’s most widely used consumer product, and engagement is key to retention. First, personalized responses could make interactions feel more tailored by letting users set preferences, increasing repeat usage. Second, better conversation memory would improve usability, reducing friction for returning users.

Finally, multimodal capabilities (text, voice, and image) would make ChatGPT more interactive, expanding use cases. I'd measure success through retention rates, session length, and user satisfaction scores while ensuring these features don’t compromise response speed or accuracy."

Round #8. Wrap-Up Questions (Final Check-In, Zoom Call)

This final check-in is your chance to tie everything together and make sure there’s a strong mutual fit. You’ll likely be asked a few last questions to confirm your alignment with OpenAI’s mission and role expectations. It’s also a great opportunity for you to ask any final questions, get clarity on the team, and leave a lasting impression before decisions are made.

Common questions here include:

      19. “What do you believe is the most significant challenge facing AI product managers today?”
      20. “How do you ensure that cross-functional teams remain aligned and motivated throughout a product's development lifecycle?”

How to Prepare

Well done, you’ve essentially made it to the end. However, it’s not time to relax just yet, as you’ll typically need to go through a final check-in Zoom call. This will usually happen around a week before the final decision is made. 

Be ready to answer thoughtful questions about AI challenges, leadership, and product management while reinforcing why you’re excited about the role. This is also your last chance to ask meaningful questions—about the team, company culture, or what success looks like in this role. 

For instance, you could answer Question #19 “What do you believe is the most significant challenge facing AI product managers today?” in the following way:

"AI moves fast, and one of the biggest challenges for PMs is making sure innovation doesn’t outpace responsibility. Just because we can build something doesn’t always mean we should. There’s pressure to move quickly, but fairness, transparency, and trust have to come first. 

Things like biased training data or unclear user expectations can cause real problems, so PMs need to stay ahead of those risks. For me, it’s about building AI products that aren’t just powerful but actually useful and responsible."

Ending on a strong note can leave a lasting impression and help you stand out from other candidates.

Final Thoughts: Your Path to Landing a PM Role at OpenAI

The above examples are sneak peeks of our OpenAI Interview Questions Database. If you can download the full list of OpenAI interview questions here to prepare for the most exciting jobs at OpenAI. 

 By following this guide and applying Dr. Nancy Li’s strategies, you’ll be well-equipped to tackle the toughest parts of the interview process. To date, she’s helped over 1500 product managers land high-paying product manager jobs in MAANG companies and unicorn startups, For exclusive insights, check out Dr. Nancy Li’s YouTube Channel and her blog!

Alternatively, if you need help preparing for your upcoming product manager interviews at OpenAI or other unicorn startups, you can book a 1:1 coaching call with Dr. Nancy Li by sending your request here. Joining Dr Li’s newsletter mailing list is also a great way to get exclusive PM job referrals and interview tips. 

All that remains to be said is Good luck, and go land that dream job!