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Openai·Backend Engineer·Technical Phone Screen·Senior

Senior
Jun 2026

Summary

Interviewed for a backend role at OpenAI and the whole thing basically centered on one deep project walkthrough. They wanted you to own the conversation, not just answer questions, which I was not fully prepared for.

Questions Asked (1)

Q1

Walk us through one of your most representative projects in depth, covering the scope, your role, technical decisions, how it touched different components, and the trade-offs you made along the way. Be ready to defend your choices.

System DesignTechnical Trade-offsAdaptability & Ambiguity
Author's notes

This is the kind of question that sounds easy until you're actually in it and realize they want you to lead, not just respond.

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AI HintsAI Generated

Suggested Approach

Choose a project that showcases end-to-end ownership and meaningful technical complexity, then narrate it as a story with clear context, decisions, and outcomes. Focus on the 'why' behind your choices and explicitly discuss trade-offs, including what you'd do differently now.

Pro tip: Frame trade-offs as conscious decisions driven by constraints (time, scale, team) rather than mistakes, and quantify impact with metrics to show you think like an owner.

1. Set the Context and Scope

Briefly describe the project's goal, scale (users, QPS, data volume), and constraints (timeline, team size, legacy systems). This grounds the interviewer and shows you understand the big picture.

2. Clarify Your Role and Ownership

State your specific responsibilities and contributions, emphasizing areas where you led design or implementation. Avoid vague 'we' statements; use 'I' to highlight your impact.

3. Walk Through Technical Decisions

Explain key architectural choices (e.g., database, caching, API design) and why you made them. Connect decisions to requirements and constraints, and mention alternatives considered.

4. Discuss Cross-Component Impact

Describe how your work touched other parts of the system (e.g., frontend, data pipelines, infrastructure) and how you collaborated with other teams. Highlight any integration challenges and how you resolved them.

5. Analyze Trade-offs and Outcomes

Explicitly state the trade-offs you made (e.g., consistency vs. availability, speed vs. quality) and their consequences. Share measurable results and lessons learned, including what you'd change.

Key Points to Mention

  • Scalability and performance considerations (e.g., horizontal scaling, load balancing, latency optimization)
  • Data modeling and storage choices (e.g., SQL vs. NoSQL, sharding, indexing)
  • API design and versioning (e.g., REST vs. gRPC, backward compatibility)
  • Observability and monitoring (e.g., logging, metrics, tracing, alerting)
  • Security and reliability (e.g., authentication, rate limiting, fault tolerance)
  • Trade-offs between consistency, availability, and partition tolerance (CAP theorem) or other relevant trade-offs

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