Summary
Alexander Zotov is a seasoned AI and engineering leader with 11+ years of focused experience building production-grade NLP and conversational AI systems, now leading AI engineering at Responsiv AI from Austin. He specializes in applied LLM work for legal domains—RAG, high-precision retrieval, controlled generation with citations, contrastive learning, and bespoke model architectures—bridging research techniques with inference-time learning and scalable serving stacks. Previously he led NLP at Relyance AI and built advanced conversational NLU at Meta and Microsoft, contributing to Cortana-era semantic parsing, knowledge graphs, and large-scale ML platforms. Alexander pairs deep academic roots in applied mathematics and CS with decades of hands-on systems engineering, from Azure ML experimentation platforms to vector stores and fine-tuning pipelines. Colleagues describe him as the kind of leader who moves quickly from novel model ideas to auditable, high-precision legal workflows—an uncommon mix of production rigor and cutting-edge generative AI craft.
11 years of coding experience
29 years of employment as a software developer
Master’s Degree Applied Mathematics and Computer Science, Master’s Degree Applied Mathematics and Computer Science at Belarusian State University
English, Russian