Summary
Duncan Rutland is a seasoned cloud-native engineering leader with over a decade of experience designing and delivering scalable platforms, from Kubernetes-based geospatial systems to enterprise-grade cloud migrations. He combines product vision and hands-on execution—leading roadmaps, architecting solutions, and shipping POCs that blend ML/AI with real-time data ingestion and visualization. As a founder and head of engineering he proved novel ML techniques on geologically sequestered CO2 projects and has repeatedly demonstrated the business value of LLMs for domain-specific document understanding. Comfortable operating at the intersection of DevOps, SRE, and data engineering, he has driven platform adoption at organizations ranging from startups to Google and H-E-B. Meticulous and strategic, he’s equally at home mentoring distributed teams as he is authoring high-quality technical documentation and tooling to accelerate developer velocity. Based in New Braunfels, Texas, he has a track record of turning experimental ML ideas into production-ready capabilities that solve hard energy and geospatial problems.
10 years of coding experience
25 years of employment as a software developer
English