One thing I've noticed is that DSA is rarely a major focus unless the role also involves core Software Engineering.

The interviews tend to focus more on:

Building AI agents and multi-agent systems

RAG pipelines, retrieval strategies, and evaluation

LangChain, LangGraph, and tool calling

LLMs, prompt engineering, and context management

Production deployment, debugging, and system design

Projects you've actually built and the engineering decisions behind them

Of course, the interview process varies by company and role, but understanding how to build, debug, and ship AI systems can make a real difference.

For people interviewing for GenAI/Agentic AI roles, what has your experience been like? Are companies focusing more on DSA or practical AI engineering?

One thing I've noticed is that DSA is rarely a major focus unless the role also involves core Software Engineering.The interviews tend to focus more on:Building AI agents and multi-agent systemsRAG pipelines, retrieval strategies, and evaluationLangC

Interview Experience | GenAI & Agentic AI Roles | Mid-Sized Companies