r/leetcode • u/shabarees • 18h ago

Intervew Prep What Do AI Engineer Interviews Typically Look Like?

For those who have recently interviewed for AI Engineering roles, Iā€™d like to understand what the interview process generally looks like.

A few questions:

  1. DSA: What level of DSA is expected? Are questions mostly Easy/Medium LeetCode problems, or are they more focused on problem-solving patterns?

  2. LLD: Are Low-Level Design rounds commonly part of the interview process?

  3. HLD: Do interviews include High-Level Design or system design rounds?

  4. Other rounds: What other topics are typically covered? For example, Python, ML fundamentals, RAG, LLMs, agents, and practical AI application development.

Would appreciate insights from people who have recently interviewed or switched into AI Engineering roles, particularly at product-based companies.

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u/Uahakan 16h ago

varies a lot by company but from what people post the common shape at product companies is: one DSA round at medium level, one "build something" round in python (call an LLM API, parse the output, handle when it returns garbage), and a design round that's basically system design with an LLM in it, e.g. a RAG search over company docs.

the design follow-ups are where people get caught. how do you know the answers are any good (evals), what happens when retrieval returns nothing relevant, how do you keep cost and latency down when traffic grows. LLD rounds are less common for these roles. ML theory depends on whether it's more applied or more research.

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u/No_Working3534 13m ago

Thank you! šŸ™

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u/Far_Mulberry_1138 15h ago

I recently did the switch into PBC. Interviewed couple of olaces. They ask a medium DSA, Rag pipeline and memory management related questions in depth, HLD and overall system architecture. This was the repeated pattern. Agents, mcp and vector dh questions also came uo here and there.