AI Interview Question Bank
Curated questions on system design, prompt engineering, RAG, LLM evaluation, and AI agents — with walkthroughs, follow-ups, and the kind of detail that actually helps you prep.
Browse by Category
AI Agents & Tool Use
Autonomous AI agents, function calling, planning architectures, and multi-agent systems.
AI System Design
End-to-end design of AI-powered systems — from architecture to deployment.
LLM Evaluation & Ops
Testing, monitoring, and operating LLMs reliably in production environments.
Prompt Engineering
Designing, evaluating, and optimizing prompts for real-world LLM applications.
RAG & Retrieval
Retrieval-Augmented Generation architectures — combining search with LLMs for grounded, accurate AI.
All Questions(9 of 25)
Design an AI Agent That Can Book Travel End-to-End
Design a multi-step AI agent that books flights, hotels, and transportation — covering tool design, planning loops, error recovery, and user confirmation.
Read questionDesign a Multi-Agent System for Software Development
Design a multi-agent system where specialized agents collaborate on software development — covering orchestration, communication, coordination, and failure modes.
Read questionDesign an AI-Powered Code Review System
Design a system that uses LLMs to automatically review pull requests — identifying bugs, style issues, and suggesting improvements at scale.
Read questionDesign a Real-Time Content Moderation Pipeline Using LLMs
Design a scalable content moderation system that uses LLMs to detect harmful content in real time while minimizing false positives and latency.
Read questionHow Would You Architect a Multi-Model AI Gateway?
Design a unified gateway that routes requests across multiple LLM providers, handles fallbacks, enforces rate limits, and tracks costs per team.
Read questionHow Would You Detect and Handle LLM Output Regressions?
Build a system to detect when LLM output quality degrades — covering statistical monitoring, automated quality checks, and incident response.
Read questionHow Do You Handle Model Version Upgrades Without Breaking Production?
A safe, systematic approach to upgrading LLM model versions in production — from pre-upgrade evaluation to canary deployment and rollback.
Read questionCompare Few-Shot Prompting vs. Fine-Tuning for a Classification Task
Understand when to use few-shot prompting versus fine-tuning for classification — covering cost, data requirements, latency, and when each approach wins.
Read questionDesign a Hybrid Search System Combining Semantic and Keyword Search
Design a search system that combines dense vector search with sparse keyword search — outperforming either approach alone through intelligent score fusion.
Read questionPrep the coding round too
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