The Coding Round
Explore how to tackle OpenAI Forward Deployed Engineer coding rounds with production-grade code practices. Understand how to define problem contracts, validate inputs, handle errors, and communicate your approach clearly during pair programming or technical tests. Learn to create reliable solutions that meet real integration needs and prepare you for practical coding tasks under interview pressure.
The task looked easy. A request expects three tool calls, c1, c2, and c3. Three results have arrived, possibly out of order. Return their payloads in call order.
The candidate checked that three records had arrived for three expected calls, built a dictionary keyed by call ID, and returned the values. Twelve minutes, clean code, one test passing.
The interviewer added one input: c1:A, c1:X, c2:B. Three records for three calls, so the length check passed. The dictionary quietly overwrote A with X. And c3 was missing, so the lookup crashed on the way out. The function had no idea which promise it was supposed to keep.
FDE candidates report coding stages that look like this: small, practical problems close to real integration work, not algorithm puzzles. The difficulty is deciding what must be true before the function returns, then proving the code enforces it while explaining each choice out loud.
What does the coding stage look for?
OpenAI’s interview guide lists pair coding, take-home projects, and technical tests among possible formats, and says formats vary by team. For engineering interviews, it says OpenAI generally looks for well-designed solutions, high-quality code, optimal performance, and good test coverage, and that interviews aim to understand how candidates approach problems and communicate their reasoning. ...