Interview kits

Interview questions with worked answers, asked the way an interviewer asks them and scored the way an interviewer listens.

Nine kits, one per role

Each kit is a bank of interview questions with worked answers. For now they open on practicai.in, where you buy and read them; your account here is not needed there.

Free guide · 21 slidesDebugging AI SystemsNon deterministic output, no stack trace, five components that can each fail silently. Here is how to find the actual problem.Open the guide
22 sections · 112 lessons · 500+ questions

AI Engineer Interview Kit

500+ structured questions from statistics to GenAI system design.

  • Statistics and mathematics for AI
  • Machine learning fundamentals
  • Transformers: architecture and training
  • Large language models
  • and 5 more

For AI, ML and GenAI engineers, LLM engineers, agent developers, and software engineers moving into AI roles.

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58 lessons · 170+ questions

RAG Interview Mastery Bundle

170+ questions across the whole retrieval-augmented generation ecosystem.

  • RAG fundamentals and core components
  • Frameworks, tools and implementation
  • Production RAG systems and architecture
  • Use cases: legal, healthcare, enterprise knowledge
  • and 1 more

For AI and ML engineers preparing for GenAI or LLM roles, data scientists moving into GenAI, and engineers building RAG applications.

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6 sections · 40 lessons · 175+ questions

Agentic AI Industry Interview Mastery

175+ questions on agent architectures, production systems and design scenarios.

  • Agent fundamentals and architecture
  • Agent frameworks and ecosystem
  • Agent production systems
  • Agent use-case design
  • and 1 more

For AI, ML and LLM engineers, GenAI developers, and students preparing for AI system design interviews.

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6 sections · 6 lessons

AI System Design

Designing real-world AI systems at scale, the way interviews ask for it.

  • Foundations
  • Designing LLM-based systems
  • RAG system design
  • Agent system design
  • and 2 more

For AI and ML engineers, backend engineers transitioning to AI, and anyone who has to design and scale AI systems in production.

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6 sections · 33 lessons · 220+ questions

LLMOps: Production AI Systems

The whole LLMOps lifecycle, from architecture to monitoring and cost.

  • LLM foundations
  • Development and experimentation
  • Deployment and infrastructure
  • Monitoring, evaluation and observability
  • and 2 more

For ML engineers, backend and platform engineers, data scientists and AI architects preparing for LLMOps and AI engineering roles.

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14 volumes · 625+ questions

MLOps Engineer (Classical) Interview Kit

625+ curated questions across fourteen volumes of production MLOps.

  • Foundations and the production mindset
  • Data engineering for MLOps
  • Experiment tracking and model lifecycle
  • CI/CD/CT for machine learning
  • and 4 more

For Engineers preparing for a first MLOps role, ML engineers moving into MLOps, platform engineers, and seniors preparing for staff-level interviews.

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4 sections · 24 lessons · 130 questions

DSA for AI Engineers

150 questions that tie data structures to RAG pipelines and agent memory.

  • Time and space complexity
  • Core patterns, asked as concepts
  • Scenario questions
  • Coding problems

For AI and ML engineers, data scientists moving into ML roles, students preparing for AI technical interviews, and engineers moving into GenAI systems.

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7 sections · 50 lessons

AI Security, Safety and Governance

How production AI systems break, and how to design ones that do not.

  • Foundations and the attack surface
  • Attack techniques
  • Defence and guardrails
  • Secure AI system design
  • and 2 more

For AI and ML engineers, data scientists, backend engineers, and anyone responsible for securing and deploying AI in production.

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11 volumes · 360 questions

AI Product Manager Interview Kit

360 questions on AI product decisions, metrics, ethics and stakeholders.

  • AI PM fundamentals and product thinking
  • Metrics and success for AI products
  • Strategy and roadmapping
  • Responsible AI and data strategy
  • and 3 more

For Product managers moving into AI, engineers and data scientists moving into PM roles, and senior leaders targeting advanced positions.

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See all kits on practicai.in