OpenAI PM candidates report a recruiter call, a hiring manager conversation, a written or take-home exercise, and a multi-conversation final loop, with questions tied to OpenAI's products and mission.
$290K
Avg. Base Comp
$759K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
Candidates describe the OpenAI Product Manager interview as a sequence that usually opens with a recruiter call and a hiring manager conversation. Several then mention a written assessment, take-home case, or roadmap exercise, followed by a final loop of back-to-back conversations. One candidate said the broader process can stretch to five stages over six to ten weeks, while another described several rounds spanning a few weeks.
Many questions are tied to OpenAI itself. One candidate was asked whether a feature should live inside ChatGPT or launch as a separate product. Another was asked what goal to set for an AI-only social network. A third was asked how to measure success for OpenAI and what to do if instrumentation went down, and also how to strengthen engagement with the developer ecosystem. A platform-versus-standalone decision framework is a sensible thing to have ready.
Motivation comes up repeatedly. Candidates report being asked why OpenAI specifically, and one was also asked why they left their current job. Others describe classic PM prompts, such as juggling conflicting priorities and what makes a PM effective. One candidate reports a culture round with a provocative hypothetical about AI taking over, and another reports systems design and coding sessions in the onsite.
Most outcomes in the evidence are rejections, and some candidates say feedback was sparse. Stages and content vary by team, so treat this as a picture of what people have seen rather than a fixed format.
Synthesized from 7 candidate reports by our editorial team.
Had an interview recently?
Share your experience. Unlock the full guide.
Real interview reports from people who went through the OpenAI process.
I interviewed for a Technical Program Manager role, so this is from the TPM side rather than product management. The first stage was a scenario-based interview. The interviewer gave me a project to work through and asked how I would tackle it. The core of the problem was competing demands from cross-functional partners, and the prompt was nuanced enough that I spent a good part of the conversation trying to work out what the interviewer was looking for. My advice is to ask clarifying questions about goals, constraints, and who has the final say before you commit to a plan. I did not receive an offer. I don't have details on any rounds after this first stage.
Prep tip from this candidate
Practice walking through a project scenario where cross-functional demands compete, and ask clarifying questions about the interviewer's expectations before laying out a plan, since this scenario was hard to read.
Share your own interview experience to unlock all reports, or subscribe for full access.
Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
| Question | |
|---|---|
| Google Maps Improvement | |
| Instagram TV Success | |
| Group Success | |
| Hurdles In Data Projects | |
| Skewed Pricing | |
| Unlimited Plan Abuse | |
| LLM Enterprise Search | |
| Spanish Scrabble | |
| Moving Window | |
| Causal Inference Without A/B | |
| Transformer Encoder Layer | |
| Facebook Story Success | |
| Scalable Data Pipelines | |
| Swipe Payment API | |
| Weighted Average With Missing Dates | |
| Trial Test Analysis | |
| Statistically Significant Test | |
| 2nd Highest Salary | |
| Empty Neighborhoods | |
| Top 5 Turnover Risk | |
| Employee Salaries | |
| Top 3 Users | |
| Experiment Validity | |
| Top Three Salaries | |
| Closest SAT Scores | |
| Last Transaction | |
| Size of Joins | |
| Button AB Test | |
| Monthly Customer Report |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report opening with a recruiter call, one lasting about 30 minutes, covering background, role fit, and basic screening. One was asked why they wanted to join OpenAI and why they left their current job. Prepare specific, personal answers rather than general excitement about AI.
Candidates describe a hiring manager conversation that digs into past projects and decisions. One found it conversational, with questions on conflicting priorities and the most important PM skills. Another was asked for specifics about projects they led. Come with concrete examples and be ready to explain your reasoning.
One candidate had two phone interviews on product sense and execution, covering how to measure success for OpenAI and what to do if instrumentation went down. The same candidate then had a longer conversation with someone in GTM about company direction and developer ecosystem engagement. Practice metrics and goal-setting for AI products.
Several candidates mention a written assessment or take-home exercise, including a roadmap-optimization scenario and a case study. One described the roadmap task as a realistic scenario that required thinking through tradeoffs and presenting a coherent strategy. Another said the case study gave time to think deeply after rapid-fire phone screens.
Candidates report a final loop of several back-to-back conversations, including a virtual super day and a loop with cross-functional partners. One described roughly four rounds over one to two days. Another reported project review, systems design, coding, behavioral, and culture sessions. Expect the mix to differ by team.
