Shayne Miel

About Shayne Miel

For over 20 years, I’ve been designing, building, and shipping AI and machine learning products at scale — from early-stage concepts to production systems used by millions. I move fluidly between leadership and hands-on engineering, equally at home architecting solutions and rolling up my sleeves to code.I thrive on systems-level thinking: turning vague ideas into clear, executable plans that align vision with reality. My passion is building products that make a real difference in people’s lives, and my work balances technical excellence with a deep understanding of human needs.Colleagues often remark on my rare combination of technical depth, clarity of communication, and empathetic leadership. Whether working with executives, engineers, product managers, or data scientists, I bridge perspectives to create technology that inspires trust — and products people love to use.

Experience

1. Principal Machine Learning Engineer

   Cisco

   Jan 2021 — Present

   an LLM-powered chat platform with RAG and tool integration in AWS, enabling customer accounts and more than 1M security professionals to manage hundreds of millions of user identities more efficiently.• Built the - into Duo’s AI Assistant, accelerating feature expansion across product lines.• Managed. for AI Assistant, introducing advanced evaluation workflows that combined automated metrics with human-in-the-loop labeling.• Designed and led development of Duo’s, improving customer security posture and reducing churn.• Developed initial vision and prototypes for Duo’s platform.• Co-chaired OpenID’s, releasing the first official specification and authoring plus open-source reference implementations to drive adoption.• Architected Duo’s, leading the engineering team through implementation.• Authored in applied AI and authentication technology.

Education

• The University of North Carolina at Chapel Hill

  Bachelor of Science (B.S.), Computer Science / Mathematics (double major)

  1998 — 2002

• Stanford University

  Graduate Certificate, Artificial Intelligence

  2016 — 2019

Skills

• Distributed Systems
• Software Development
• Python
• C/C++
• C#
• Machine Learning
• Amazon Web Services (Aws)
• Sql
• Linux
• Data Analysis
• Natural Language Processing
• Git
• Deep Learning
• Cloud Computing
• Research
• Java
• Continuous Integration
• Artificial Neural Networks
• Data Modeling
• Artificial Intelligence
• Agile Methodologies