A GenAI engineering interview is rarely pure DSA and rarely pure LLM trivia — it's usually both, plus a system-design round that expects you to reason about a real pipeline, not recite a model's parameter count.
What actually gets asked
- Classic DSA, at a level appropriate to the role — this doesn't disappear because the role has 'AI' in the title.
- System design: 'design a RAG system for X' — expect follow-ups on chunking, evaluation and failure modes, not just architecture boxes.
- Practical judgement: 'the model is hallucinating dates, what do you check first' — tests whether you've actually debugged one of these.
How to prepare for the practical-judgement questions
These aren't found in an interview prep book — they come from having actually built and broken a RAG or fine-tuning pipeline. A single well-documented project you can speak about in depth outperforms a list of tutorials you've followed.
See the GenAI engineer roadmap for 2026 and GenAI engineer interview questions.
GenAI engineer and AI product builder with 2+ years shipping production-grade AI systems: RAG pipelines, fine-tuned LLMs, hybrid retrieval and multi-modal apps across vision, speech and OCR, architected end to end from ingestion to deployment. Leads engineering for SCULT INDIA's 14-member team, founded the 500+ member TechVerse Enclave community and has mentored 200+ students. Three hackathon first prizes: Changethon 2025 (IIT Roorkee), Product Genesis at Vividhotsava 2025 (CSJMU Kanpur) and BYTEBATTLE (MeetKats).
Open to GenAI roles, hackathon judging, mentorship sessions and guest talks at colleges. Email pranjulrathour41@gmail.com.
