EngMock

Frontier AI lab · Official sources last checked 2026-08-02

Prepare for OpenAI software engineering interviews

Practice the coding, systems, AI infrastructure, and communication signals that OpenAI describes for engineering candidates, using independent EngMock scenarios grounded in public material.
Browse AI systems practiceView candidate-reported patterns
Independent preparation: EngMock is not affiliated with or endorsed by OpenAI. Officially sourced process facts are separated from candidate reports and independent practice scenarios. Interview steps vary by role, team, level, and location; always follow your recruiter's current instructions.

Officially confirmed

What OpenAI says about its process

  1. 1An introductory conversation covers your experience, motivations, goals, and fit with the role or team.
  2. 2Skills-based assessments vary by team and may include pair coding, take-home projects, technical tests, or more than one assessment.
  3. 3Final interviews typically span four to six hours with four to six people over one or two days, virtually by default with an onsite option in San Francisco.
  4. 4Engineering evaluation emphasizes well-designed solutions, high-quality code, performance, test coverage, communication, and collaboration.

Official sources

Last verified 2026-08-02. We update the page when official hiring information materially changes.

Role coverage

Roles this guide supports

Software EngineerResearch EngineerAI Infrastructure EngineerApplied AI Engineer

Practice focus

Signals to rehearse

  • Production-quality coding
  • Distributed AI infrastructure
  • LLM serving and evaluation
  • Testing and performance
  • Technical communication

Focused preparation plan

Turn the process guide into a timed mock interview

OpenAI Coding Interview Preparation

Build a coding practice loop around clear reasoning, correct implementation, validation, and deeper follow-ups—without relying on leaked or claimed official questions.

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Independent company-style practice

AI engineering scenarios relevant to OpenAI

These EngMock exercises are either original, based on public engineering themes, or adapted from candidate reports, which may be about other companies. They are not represented as official or leaked OpenAI interview questions.

Hard

Design a Multi-Tenant LLM Inference Platform

Design a global inference service for mixed chat, coding, and long-context workloads across heterogeneous accelerators, starting from one region and model.

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Hard

Design a Web Crawler

Design a scalable web crawler like Googlebot to index the internet.

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Medium

Design a Rate Limiter

Design a service to limit the number of requests a user can send to an API within a time window.

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Hard

Architecture Deep Dive on Your Past Project

Defend the architecture of a real project you built, its constraints, trade-offs, failures, and how you would redesign it today.

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Practice the underlying interview skills

Combine a live technical mock with the candidate-reported Question Bank, then use the evidence-based report to choose your next focused scenario.

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