Post by Mastering LLM (Large Language Model)

Most engineers aren’t failing GenAI interviews because they lack talent. They’re failing because they’re preparing for the wrong game. Here’s what we keep seeing: ❌ Tutorial-level depth ❌ Outdated prep questions ❌ No system design practice ❌ Vague answers like “it depends” But interviews today expect: ✅ Strong fundamentals (transformers, attention, KV cache) ✅ Real-world RAG systems (Document Digitization→chunking → retrieval → reranking → grounding) ✅ Clear trade-offs (prompt vs RAG vs fine-tuning — cost, latency, data) ✅ Structured thinking (problem → options → trade-offs → decision) That gap is why smart engineers still struggle. We’ve put together a course at Mastering LLM focused entirely on this: • 250+ real interview questions • Transformers, RAG, fine-tuning (done right) • Agents, evals, guardrails • System design drills with real scenarios Built by engineers who actually hire for these roles If you're serious about landing a GenAI role, this is the level you need to prepare at. 👉 Course link is in the comments.