fastapi-ai-interview-prep

A question bank and mock-interviewer toolkit for FastAPI + AI-engineering roles. Ten topic files hold ten questions each (100 total), every answer written to the senior signal an interviewer listens for — the production consequence or trade-off that separates "knows the API" from "has run this at scale."

Inspired by the topic coverage of FastAPI for AI Engineers (AI Engineering Insider, 2026). All questions and answers are written from scratch; this is not a reproduction of the book's question set.

What ships

• The full SKILL.md (skills/local/fastapi-ai-interview-prep/SKILL.md) — three session modes (mock interview, topic drill, self-test) and a grading rubric (correctness → senior signal → scenario method).
• Ten reference files (references/ch01-intro.md … ch10-deployment.md), one per chapter, 10 self-written Q&A each: intro/ASGI, Pydantic, endpoints, dependency injection, databases, security, testing, async, AI serving, deployment.
• One script:
  • quiz.py — draws/lists/reveals questions parsed live from the references. Stdlib only.

Quick start

cd skills/local/fastapi-ai-interview-prep

python3 scripts/quiz.py --topics              # chapters + counts
python3 scripts/quiz.py --random 5            # ask 5 (no answers)
python3 scripts/quiz.py --answer ch09-q4      # reveal one rubric
python3 scripts/quiz.py --topic ch08 --random 4 --with-answers
python3 scripts/quiz.py --random 3 --seed 42 --json   # reproducible, machine-readable

Run a mock interview by drawing questions without answers, letting the candidate respond, then revealing the rubric per id to score against the senior signal.

Cross-references

• To apply these patterns: fastapi-ai-patterns.
• To build a service: fastapi-ai-scaffold.