This one is more stressful than it sounds.
Choose a project where you made significant technical decisions and can clearly articulate the architecture, trade-offs, and failures. Structure your slide deck to tell a story: start with the problem and constraints, then walk through your design choices, what went wrong, and what you learned. Be prepared to dive deep into any aspect, emphasizing your personal ownership and how you'd approach it differently now.
Pro tip: Use the 'trade-off triangle' (e.g., consistency, availability, partition tolerance) to frame decisions, and explicitly state what you optimized for and what you sacrificed. Also, proactively mention a failure and how you mitigated it—this shows maturity and self-awareness.
Briefly describe the project's goal, your role, the team size, and the key constraints (e.g., time, scale, legacy systems). This helps the interviewer understand the environment and your responsibilities.
Present a high-level diagram of the system, highlighting the main components, data flow, and technologies used. Explain how the components interact and why you chose that architecture.
For each major decision (e.g., database choice, API design, scaling strategy), explain the alternatives considered, the pros and cons, and why you chose one over the others. Tie decisions back to the constraints.
Describe a specific failure or challenge (e.g., performance bottleneck, bug, miscommunication), how you diagnosed it, and what you changed. Emphasize what you learned and how it influenced future work.
Summarize what you'd do differently now, and clearly state your personal contributions. Highlight any leadership or initiative you took, and how this project prepared you for new challenges.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Connect your personal mission to OpenAI's mission of ensuring AGI benefits all humanity, and show how your engineering skills can contribute to solving unique challenges at scale. Emphasize your adaptability to ambiguous problems and your excitement about working on cutting-edge AI research and deployment.
Pro tip: Reference OpenAI's specific engineering challenges, such as scaling large language models or ensuring safety, and mention how you've prepared for them through past projects or self-study. Avoid generic praise; instead, show you understand OpenAI's unique culture and technical stack.
Express genuine passion for OpenAI's mission to ensure AGI benefits all humanity, and connect it to your own values and career goals.
Discuss specific technical challenges OpenAI faces, such as scaling models, safety, or deployment, and how your skills can address them.
Give examples of how you've thrived in ambiguous, fast-paced environments and how that prepares you for OpenAI's dynamic research and engineering landscape.
Mention OpenAI's collaborative, mission-driven culture and how your working style aligns with it, citing specific values or practices.
Articulate how you see yourself contributing to OpenAI's long-term goals and growing with the company.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Was not expecting them to go this deep on it.
Acknowledge the transformative potential of AGI while emphasizing a balanced, safety-first perspective that aligns with OpenAI's mission. Structure your answer to show you've thought deeply about both benefits and risks, and tie it back to your role as a software engineer—how you'd contribute to safe development.
Pro tip: Avoid making definitive predictions about AGI timelines; instead, focus on the importance of iterative deployment and learning from real-world feedback. Show humility about unknowns and a commitment to safety, which resonates strongly at OpenAI.
Briefly define AGI as AI with human-level or beyond capabilities across most economically valuable work, and note its potential to solve major global challenges.
Discuss key risks such as misuse, alignment failures, economic disruption, and concentration of power, showing awareness of both technical and societal dimensions.
Highlight the need for technical safety research, robust alignment methods, and governance frameworks to ensure AGI benefits humanity.
Explain how as a software engineer you'd contribute to safe AGI development, e.g., by building reliable systems, supporting interpretability, or fostering collaboration.
Conclude with a forward-looking, adaptable mindset: AGI is uncertain, but we can steer it responsibly through continuous learning and iteration.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Picked a real one, which I think was the right call.
Choose a real mistake with meaningful impact, but one where you owned it quickly and drove a fix. Use a structured story (context, mistake, impact, resolution, learning) that shows accountability and growth. Emphasize what you changed afterward so the interviewer sees you as someone who turns failures into better systems.
Pro tip: Pick a mistake that is significant but not disqualifying, and show that you proactively told your manager or team before it became a bigger problem—this demonstrates integrity and good judgment under pressure.
Describe the project, your role, and the constraints so the interviewer understands why the mistake mattered. Keep it to 2-3 sentences and avoid unnecessary technical detail.
Say exactly what you did wrong without hedging, blaming others, or minimizing it. Use 'I' statements and acknowledge the impact on users, teammates, or timelines.
Describe how you found out, who you informed, and the concrete steps you took to fix or mitigate the issue. Highlight any communication with stakeholders and any trade-offs you made.
Explain how the situation was resolved and what the final result was. If possible, include a metric or specific improvement that shows the fix worked.
Describe what you learned and what you changed in your process, tooling, or habits to prevent similar mistakes. Connect it to how you now approach ambiguity or conflict.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
I went with a leadership disagreement because I thought it showed more range.
Choose a disagreement where you had a strong technical or product rationale, but ultimately prioritized the team's success and user impact. Show how you listened, articulated your concerns with data, and either influenced the decision or committed fully once a decision was made. Emphasize the positive outcome and what you learned about collaboration.
Pro tip: At OpenAI, demonstrating that you can disagree respectfully and then commit to the chosen path is crucial—show that you optimize for the mission, not for being right.
Briefly describe the project, the team, and the decision that caused disagreement. Keep it concise and focused on the technical or strategic stakes.
Clearly state your position and the opposing view, highlighting that it was a healthy debate about ideas, not personalities. Mention the data or reasoning behind your stance.
Describe how you listened actively, asked questions, and presented your case with evidence. Emphasize your openness to being wrong and your focus on finding the best solution.
Explain how the disagreement was resolved—whether you persuaded others, compromised, or deferred to the decision. Show that you supported the final decision fully, even if it wasn't yours.
Share the outcome and what you learned about communication, teamwork, or decision-making. Highlight how this experience improved your ability to collaborate.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Choose a specific instance where you received tough feedback or failed to deliver, and focus on how you responded and what you learned. Be honest about the mistake or feedback, but emphasize the actions you took to improve and the positive outcome that resulted.
Pro tip: Show that you actively seek feedback and can separate your ego from your work; at a company like OpenAI, intellectual humility and rapid iteration are highly valued.
Briefly describe the project or situation, including your role and the stakes involved, so the interviewer understands the background.
Clearly state what the tough feedback was or how you failed to deliver, without sugarcoating or blaming others.
Detail how you processed the feedback, what you did to address the issue, and any specific steps you took to improve or recover.
Share the positive results that came from your actions, such as improved performance, successful delivery, or stronger relationships.
Summarize what you learned and how you've applied that lesson to prevent similar issues or to grow professionally.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Describe a collaborative, proactive working relationship with PMs, emphasizing shared goals and regular communication. Then, explain a structured approach to handling pushback: listen, understand the underlying concern, and use data and user impact to find a mutually agreeable solution. Highlight flexibility and a focus on outcomes over being right.
Pro tip: Frame pushback as a valuable opportunity to stress-test your ideas and align on priorities; show that you can disagree and commit when necessary, but also know when to escalate with evidence.
Explain how you build a strong working relationship with PMs through regular syncs, shared understanding of goals, and mutual respect for each other's expertise.
When pushback occurs, actively listen to the PM's concerns, ask clarifying questions, and seek to understand their perspective and underlying priorities.
Clearly articulate your reasoning, backing it with data, technical trade-offs, and user impact, while remaining open to alternative solutions.
Work together to find a compromise or alternative that addresses both technical and product concerns, focusing on the best outcome for the user and business.
If alignment can't be reached, involve a manager or escalate with a clear summary of trade-offs; otherwise, disagree and commit to support the team's decision.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.