AI Evaluation Engineer vs AI Fallback & Escalation Designer

A AI Evaluation Engineer Only

• Designing evaluation metrics and benchmark suites for LLM and generative AI outputs
• Python proficiency for writing evaluation scripts, data pipelines, and scoring harnesses
• Statistical analysis including hypothesis testing, confidence intervals, and inter-rater reliability
• Prompt engineering for automated evaluation and synthetic test-case generation
• Understanding of AI failure modes: hallucination, sycophancy, reward hacking, jailbreaking
• Human evaluation design including rubric creation, annotator calibration, and bias mitigation
• Regression testing and A/B evaluation frameworks for model version comparison
• Red-teaming and adversarial testing methodologies for safety and alignment