Context Engineering for AI Engineers Interview Preparation Handbook

Prompt Engineering got you a demo. Context Engineering gets you hired at $350k–$600k and keeps your system alive in production.

Context Engineering for AI Engineers is the definitive architectural field guide and system-design interview handbook for engineers who have moved beyond toy prompts and need to build resilient, low-latency, mission-critical AI runtimes. Master hybrid retrieval, agentic memory, KV-cache economics, tool sandboxing, and pass the most grueling AI Staff/Principal interviews.

What’s Inside: The Complete Package

• 15 Comprehensive Chapters: From Transformer attention mechanics and KV-cache VRAM sizing to distributed multi-agent context buses and Context-as-a-Service (CaaS).
• 75 Hardcore Senior & Staff Interview Questions: Deep architectural prompts, failure-mode post-mortems, and comprehensive Staff-level sample answers evaluating latency, trade-offs, and failure recovery.
• Rigorous Mathematical Foundations: Exact formulas for BM25 Okapi, L2L2​-normalized dense vector cosine similarity, Reciprocal Rank Fusion (RRF), Ebbinghaus exponential memory decay, and KV-cache memory sizing
• Open-Source Companion Codebase: A pure Python standard-library reference architecture with zero heavy dependencies, featuring an interactive Streamlit UI test harness (github.com/lamhotsiagian/context-engineering).