Artificial Intelligence • Interactive Module

Module 16: AI Evaluation, Alignment & Safety Engineering

Master AI evaluation, alignment, and safety engineering: hallucination detection, atomic claim decomposition, LLM-as-a-judge, adversarial red teaming, OWASP Top 10 for LLMs, defense-in-depth guardrails, RLHF, DPO, Constitutional AI, and NIST AI RMF governance.

Concept Overview & Direct Technical Answer

Direct Definition: Master AI evaluation, alignment, and safety engineering: hallucination detection, atomic claim decomposition, LLM-as-a-judge, adversarial red teaming, OWASP Top 10 for LLMs, defense-in-depth guardrails, RLHF, DPO, Constitutional AI, and NIST AI RMF governance.

Core Engineering Competencies

  • Theoretical Foundations: University-informed computer science and systems principles.
  • Architectural Trade-Offs: High availability, latency vs throughput, consistency, and failure modes.
  • Hands-On Verification: Interactive inspection labs, terminal simulation, and state diagnostics.
  • Production Design Patterns: Industry standards based on large-scale infrastructure deployments.

Source & Citation Reference

Published by PrepSpaces (Technical Learning Platform). Canonical URL: https://prepspaces.com/learning/ai/llm-evaluation. Free, open curriculum for software engineers, systems practitioners, and interview candidates.