AI Engineer Interview : RAG & Agents
3-6 years experience ~2 hours 6 Topics
Checklist covers LLM Fundamentals, Prompting, Embeddings and Vector Databases, Retrieval-Augmented Generation, Fine-Tuning, Agents
What You'll Learn
Before You Read This
You have built a RAG chatbot that actually retrieves the right chunk. You have shipped an agent that calls tools without falling over.
Tier 1 - Fundamentals Checklist
No answers given. These are the floor, not the ceiling.
Tier 2 - Real Interview Questions
RAG Under Pressure Design a RAG system for a fintech customer support product that answers questions from internal policy documents.
Tier 3 - Scenario Round
These are live problems interviewers put in front of you and watch how you think. There is no single correct answer. Q25.
Behavioral Round
12 behavioral questions with full answers covering ownership, pushback, and what interviewers are actually evaluating.
Salary Reference
These are broad, market-oriented ranges, not guaranteed offers.
Skills You'll Master
Curriculum Index6 topics
Before You Read This
You have built a RAG chatbot that actually retrieves the right chunk.
Tier 1 - Fundamentals Checklist
No answers given. These are the floor, not the ceiling.
Tier 2 - Real Interview Questions
RAG Under Pressure Design a RAG system for a fintech customer support product that answers questions from internal...
Tier 3 - Scenario Round
These are live problems interviewers put in front of you and watch how you think. There is no single correct answer.
Behavioral Round
12 behavioral questions with full answers covering ownership, pushback, and what interviewers are actually evaluating.
Salary Reference
These are broad, market-oriented ranges, not guaranteed offers.
Career Impact
Roles this pack prepares you to interview for.
- High Demand
AIOps Engineer
Rs 20L - Rs 45L a year
Next Modules
Practice on the Coding Sheet
Not a software engineer sheet. Every problem comes from real DevOps, SRE, Platform and Cloud interviews, from your first script to a system you build yourself.
Open the Coding SheetFrequently Asked Questions
Yes - every question here reflects patterns reported from real 2026 interview loops at AI-first companies, not questions invented from general LLM knowledge.
The content reflects how AI engineer interviews look as of 2026, when the emphasis shifted toward RAG, agents, and production judgment rather than pure LLM internals trivia.
This pack targets mid-level AI engineers with a few years of experience building RAG pipelines, agents, or other production LLM systems.
It helps, but is not required. Each answer explains the reasoning in plain language, so it also works as a structured way to build that judgment before your first real production incident.