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Openai·Software Engineer·Technical Phone Screen·Senior

Senior
Jun 2026

Summary

Project deep-dive round at OpenAI for an iOS Engineer role. The whole thing was one long conversation about a single past project, and they went surprisingly deep on every layer.

Questions Asked (1)

Q1

Walk me through a significant project you've owned end-to-end: the problem it solved, your specific role, the key design decisions you made, the technical challenges you hit, and what the actual impact was.

Technical Trade-offsSystem DesignAdaptability & Ambiguity
Author's notes

This is the whole round basically.

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AI HintsAI Generated

Suggested Approach

Choose a project where you had clear ownership and can quantify impact. Structure your answer as a narrative: problem, role, decisions, challenges, impact. Emphasize trade-offs and how you navigated ambiguity, especially in a fast-paced environment like OpenAI.

Pro tip: Focus on the 'why' behind your decisions, not just the 'what'. Show how you balanced competing priorities (e.g., speed vs. quality) and how you adapted when things changed.

1. Set the Context

Briefly describe the problem, why it mattered, and the project's scope. Mention any constraints (time, resources, technical debt).

2. Define Your Role

Clearly state your specific responsibilities and how you contributed to the team. Avoid vague statements; be concrete about what you owned.

3. Explain Key Decisions

Walk through 2-3 critical design or technical decisions. For each, explain the options considered, the trade-offs, and why you chose that path.

4. Discuss Challenges & Adaptations

Describe a significant technical or organizational challenge. Explain how you diagnosed it, what you changed, and what you learned.

5. Quantify Impact

Share measurable outcomes (e.g., performance improvements, user growth, cost savings). If possible, tie it to broader business or user goals.

Key Points to Mention

  • The problem's significance and why it was worth solving
  • Your specific role and ownership (e.g., led design, implemented core component)
  • Key design decisions and trade-offs (e.g., build vs. buy, consistency vs. availability)
  • Technical challenges and how you overcame them (e.g., scaling, debugging, integration)
  • Adaptability to ambiguity or changing requirements
  • Quantifiable impact (e.g., latency reduction, revenue increase, user adoption)

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.