AI Engineer & FDE Interview Prep: 160+ Exercises

About this course

Forward deployed engineer interviews don't look like regular software interviews. You'll still write code, but the code is usually about a customer's messy reality: a CSV export with broken rows, an API that rate-limits you, a pipeline someone else wrote that reports the wrong numbers. Then come the rounds that catch strong engineers out: breaking down a vague business problem out loud, learning an unfamiliar SDK in the room, calming a customer whose agent just issued wrong refunds, and defending a design to a hiring manager. This course prepares you for all of them.

Why a course for this role specifically? Because the skills overlap with backend and AI engineering but the emphasis is different. An FDE is judged on how quickly they can make something work inside someone else's systems and constraints, and how clearly they explain it to people who aren't engineers. Practicing generic algorithm puzzles doesn't build that. Practicing customer-shaped problems and conversations does.

It combines 160 coding exercises in the Python editor built into the course, 13 AI mock interviews and 4 take-home projects. Every coding exercise is a small customer scenario with a function or class to complete, checked by automated tests when you submit. No API keys or cloud accounts are needed.

The coding exercises, by round

Python fluency and messy data. The first 20 exercises cover the everyday code an FDE writes in week one on a customer site: normalizing chat messages, deep-merging configs, batching for an API, avoiding float errors in invoice totals, loading transactions while skipping bad rows, normalizing mixed date formats, parsing currency, flattening nested JSON for a spreadsheet, detecting a CSV delimiter and finding why an Excel export won't total.

Data modeling and aggregation.

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