About
Xiaojun Wang / 王晓军
I have been focused on AI Testing and AI Quality Engineering for several years, working at the intersection of software quality assurance and artificial intelligence. My work spans building evaluation frameworks, developing testing methodologies for intelligent systems, and educating engineering teams on AI quality practices.
The core question that drives my work: How do we build reliable, trustworthy AI systems that we can test, measure, and improve systematically?
Areas of Work
- AI Testing — Developing testing frameworks and strategies for AI-powered applications, from unit-level model tests to end-to-end pipeline validation.
- AI Quality Engineering — Engineering quality gates, monitoring systems, and reliability metrics for AI systems in production.
- AI Quality Platform — Designing and building integrated platforms for AI quality management — orchestrating tests, collecting evaluation results, and enabling data-driven quality decisions.
- LLM & Agent Testing — Building evaluation suites for large language models and autonomous AI agents — measuring reasoning, safety, tool use, and task completion.
- AI Education — Creating learning resources and training programs to help engineering teams adopt AI quality practices.
- Intelligent System Testing — Exploring testing approaches for adaptive, learning-based systems that do not fit traditional software testing models.
Connect
I share technical writing and project updates on this site. You can also find me on GitHub and LinkedIn.