AI Adaptive Learning Engineer vs AI Agent QA Engineer

B AI Agent QA Engineer Only

• LLM output evaluation and scoring (both automated and human-in-the-loop)
• Prompt engineering for test case generation and evaluation criteria
• Python test automation with pytest, parametrize patterns, and CI/CD integration
• Agent architecture understanding (ReAct, tool-use, multi-agent orchestration)
• Non-deterministic system testing strategies and statistical significance analysis
• Red-teaming, adversarial testing, and safety evaluation for AI agents
• Observability and tracing for LLM pipelines (spans, traces, token-level debugging)
• Regression testing and benchmark management for prompt and model changes