Tech · AI & Machine Learning

Cracking the AI Engineering and Agentic AI Interview

Written by Zeeshan Adil

12 h 31 min · 13 parts · 79 chapters

From chapter 1, 12 h 31 min

Get ready for AI engineer, LLM engineer and agentic AI interviews at remote-first companies. Learn RAG, agents, evaluation, async Python services, LLM serving on GPUs and production operations from the foundations up to senior depth, practise every round of the interview loop with model answers and follow-up probes, then build, evaluate and defend your own small RAG plus agent service.

Read the course: the same chapters with diagrams, labs and quizzes.

Chapters

Part 1 · The AI engineering interview loop

38 min

Part 2 · LLM foundations for application engineers

44 min

Part 3 · RAG fundamentals

55 min

Part 4 · Advanced retrieval

54 min

Part 5 · Evaluating RAG and LLM systems

55 min

Part 6 · Agents and tool calling

39 min

Part 7 · Stateful agents with LangGraph

59 min

Part 8 · MCP, prompt injection and guardrails

37 min

Part 9 · Python service engineering

1 h 10 min

Part 10 · Production: tracking, tracing, deployment and monitoring

52 min

Part 11 · Mock interviews: every round

2 h 4 min

Part 12 · Capstone: build, evaluate and defend

1 h 7 min

Part 13 · LLM inference, serving and GPU capacity

59 min