Summary
Kelvin Tan is a seasoned search and AI leader with nearly two decades of deep experience across query understanding, semantic search, knowledge graphs, and learning-to-rank systems. He has led AI and LLM strategy and engineering at SearchStax and built search teams and pipelines from the ground up at companies like Vetted and Homethinking, delivering production-grade solutions including BERT embeddings, RAG prototypes, and automated search quality regression testing. Equally comfortable in hands-on engineering and strategic roles, he has architected large-scale crawlers and Solr/Lucene integrations, as well as mentored cross-functional teams to operationalize AI across product and support. As a volunteer Head of IT he scaled a real-time virtual meeting platform during COVID, demonstrating an ability to deliver mission-critical systems under pressure. Based in the United States, he blends product-focused execution with research-driven experimentation in ML/LLMs, and balances a developer’s rigor with a family-first mindset reflected in his GitHub bio. Notably, his work spans both consulting for major clients like Atlassian and Indeed and founding-CTO level technical ownership, giving him rare end-to-end search domain expertise.
9 years of coding experience
4 years of employment as a software developer
Computer Science, Computer Science, Computer Science, Computer Science at Brigham Young University - Hawaii
Chinese, English, Malay