Summary
Dean Keesey is a Generative AI Systems Architect with 15+ years of enterprise engineering experience who designs and runs production-scale AI and automation platforms from the edge to analytics pipelines. Currently building LLM-driven architecture governance at Wells Fargo, he specializes in multi-agent coordination, context architecture, failure-mode detection, and cost-aware model routing that routinely delivers 40–60% savings. As Fractional CTO for the Masumi Hayashi Foundation he manages a 523-page site serving 30K+ annual visitors with custom WAF, webhook-driven donation flows, and analytics clean-up that filtered 92% bot traffic—an example of applying rigorous production practices to cultural technology. His work reduces complex engineering sessions (6+ hours) down to 2 via shared-memory agent orchestration and replaces dashboards with proactive GA4→BigQuery→Slack delivery, showing a bias for operational simplicity and measurable outcomes. Based in the Bay Area, he blends deep frontend roots with modern cloud/edge architectures to make agentic AI reliable, auditable, and cost-effective.
8 years of coding experience
3 years of employment as a software developer
HS diploma, National Merit Scholar, HS diploma, National Merit Scholar at School for Applied Individual Learning
BA, Art, Art History, Political Science, Sociology, BA, Art, Art History, Political Science, Sociology at Amherst College
MSEdu, Instructional Technology, MSEdu, Instructional Technology at University of Massachusetts Amherst