Summary
Rachel Bowyer is a Senior AI Engineer with 12 years of experience building AI/ML-driven, cloud-native systems for financial technology and payments. She combines deep hands-on expertise in Python, Clojure and distributed systems with practical experience deploying LLMs, RAG, Neo4j and Chroma to solve real-world problems like invoice acceleration and entity resolution. At Previse she led bi-temporal ledger refactors and raised zero-shot line-item classification accuracy from 51.5% to 83% using RAG+LLM ensembles and error models, demonstrating a rare mix of research-to-production delivery. Comfortable across architecture, DevOps and data science, she champions automated CI/CD, infosec-aware AI tooling and cross-disciplinary collaboration. Based in London, she brings a pragmatic mathematician’s mindset and a track record of turning complex regulatory and payments challenges into auditable, scalable systems.
12 years of coding experience
18 years of employment as a software developer
LPC, Law, LPC, Law at BPP Law School
GDL, Law, GDL, Law at City St George’s, University of London
BSc, Mathematics, BSc, Mathematics at University of Bristol