openskill
Interview tracksLLM / GenAI & Prompt/Context Engineering
Interview track

LLM / GenAI & Prompt/Context Engineering

From prompt and context engineering to retrieval, evaluation, fine-tuning and safety. Practice the questions teams actually ask when hiring for LLM and GenAI roles.

Curated & expert-sourced - not AI-invented
18
interviews
Easy → Hard
levels covered
~30 min
average length
Voice-led
adaptive · curated

All interviews 18

Grouped by level - start anywhere

Medium

11 interviews
Context Engineering & System Prompt Design
Curated·Technical·Medium·~30 min
Start
Hallucination: Causes, Detection & Mitigation
Curated·Technical·Medium·~30 min
Start
LLM Evaluation: Benchmarks, Metrics & Judge Models
Curated·Technical·Medium·~30 min
Start
LLM Pre-Training: Data Curation & Scaling Laws
Curated·Technical·Medium·~30 min
Start
Distributed Training Strategies for LLMs
Curated·Technical·Medium·~30 min
Start
Advanced Prompting Techniques
Curated·Technical·Medium·~30 min
Start
LLM Quantization: Methods & Trade-offs
Curated·Technical·Medium·~30 min
Start
RAG: Fundamentals & Pipeline Design
Curated·Technical·Medium·~30 min
Start
Structured Output & Function / Tool Calling
Curated·Technical·Medium·~30 min
Start
Supervised Fine-Tuning: Full Fine-Tuning & PEFT Overview
Curated·Technical·Medium·~30 min
Start
Attention Variants & Decoding Strategies
Curated·Technical·Medium·~30 min
Start