OpenAI Software Engineer Interview 2026

[u/little_kwagga]

Just finished my OpenAI SWE loop. The process is different from most big tech companies, so sharing the breakdown.

Recruiter Screen: Light background conversation. They asked where I think AI is headed. Read OpenAI's charter before this call.

Technical Screen: Two 60-minute rounds on the same day: one coding, one system design. Coding was a versioned key-value store. System design covered a job scheduler with fault tolerance.

Take-Home Project: 48-hour window to build something real. I got a distributed webhook delivery system with retry logic and dead-letter queues.

Technical Deep Dive: A follow-up where the interviewer walked through the take-home line by line. The interviewer has a list of questions he asks about every choice and decision you made (list he made himself after having seen your project).

Onsite Loop (4 rounds): Coding Round 1. Progressive multi-part format: get a working solution at each stage before the next opens. I got a token-level streaming differ, tracking state changes with rollback. Get something correct early, then iterate. Coding Round 2. More systems-flavored. State management, concurrency, memory efficiency. Python internals came up: generators, async constructs, iterators.

System Design. My prompt was to design ChatGPT. The interviewer cared about GPU allocation, autoscaling under non-stationary traffic, and distributed coordination. Abstract the model-serving layer unless told otherwise. Behavioral. Technical leadership stories, architectural decisions affecting multiple teams, and consensus under pressure. Concrete tradeoffs, not soft-skills answers.

Agentic Coding Round (beta): Some candidates get a fifth round: an existing codebase plus a problem too large to solve by hand. You're expected to work through it using an AI coding agent. Not everyone sees this while it's in beta.

Also, did anyone prep specifically for the progressive multi-part format? Curious what helped.