Summary
Daniel Dye is a seasoned software and data engineer with over a decade of experience and two decades of hands-on technical work spanning scientific programming, machine learning, DevOps, and SecOps. Currently a Google SecOps AI Engineer, he builds cloud-native security tooling and open-source projects—like Chronicle Logstory, MCP Security servers, and AI Runbooks—that bridge AI agents with real-world SOC workflows. He has deep Python and Linux expertise, plus practical experience in Go, Kubernetes, and enterprise ETL and big-data pipelines from roles at Soltra, Dark Cubed, and consultancies. Daniel’s background in quantitative geography and geoinformatics informs a strong spatial-statistics and data-visualization sensibility that surfaces in his tooling for telemetry replay and threat intelligence sharing. He is equally comfortable authoring technical documentation and shipping production-grade CI/CD and packaging solutions. Based in Tampa, he blends research-driven problem solving with pragmatic engineering to operationalize AI for cybersecurity.
14 years of coding experience