AI Engineering Interview Prep
Model answers, system-design practice and mock interviews.
80+ interview questions with strong answers across LLMs, RAG, agents, MCP, security, evaluation, production, AWS and staff-level topics — plus coding drills, a design method and a four-week mock-interview plan.
11 lessons · about 3.4 hours
What interviewers score, the answer framework, behavioral stories and eight fundamentals questions with model answers.
Ten questions with strong answers on prompt design, context engineering, injection, versioning and cost.
Ten questions on production RAG: architecture, chunking, hybrid search, reranking, evaluation, isolation and when not to use RAG.
Ten questions on autonomy, workflows vs agents, stopping criteria, loops, resumability, tools and evaluation.
Nine questions on MCP, tool registries and versioning, and when multiple agents are justified.
Nine questions on prompt injection, exfiltration, authorization, red teaming, secrets and supply chain.
Ten questions on evals, LLM judges, observability, reliability, cost, latency and incidents.
A fully worked multi-tenant RAG design on AWS plus seven design and architecture questions.
Nine questions on platforms, standards, migrations, governance, disagreements and failure stories.
Six worked coding drills (retries, similarity, RRF, dispatcher, chunker, rate limiter) and how take-homes are judged.
A four-week plan, an AI mock-interviewer prompt, a scoring rubric, three scenarios and a day-of checklist.