J E W E L L W R I G H T

Technical. Thoughtful. Pragmatic.

Technology has always been my playground. I love building systems, experimenting with AI, and designing platforms that make hard problems feel simple. Just as much, I enjoy sharing what I learn through teaching, writing, and technical enablement. Whether I'm researching reinforcement learning, architecting enterprise solutions, or leading a workshop, my goal is the same: build well, explain clearly, and leave people more capable than when they started.

Areas of expertise

My work combines technical depth with instructional design and organizational systems thinking. I focus on making AI knowledge usable for practitioners, learners, educators, and leaders. Flip a card to learn more.

AI & Machine Learning

Research: Conducted research in reinforcement learning, resilient AI systems, model training robustness, and resource distribution.

Solutioning

Architecture: Designed enterprise AI, analytics, and data solutions that transformed complex technical challenges into scalable business outcomes.

Technical Advocacy

Technologist: Creating hands-on demos, reference architectures, workshops, and developer enablement programs that accelerate technology adoption.

Teaching & Enablement

Technical Instruction: University instructor and curriculum developer focused on computer science education, workforce development, and technical certification success.

Experience

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Technical Advocate and Curriculum Developer | Remote

Served as a technical subject matter expert across Snowflake Cortex AI and Snowpark, supporting applied AI, data engineering, and real-time analytics initiatives within Academia.
Developed hands-on labs and technical solutions using Snowpark, Cortex Search, vector embeddings, and Snowflake Container Services.
Built scalable onboarding and certification enablement frameworks using Snowflake Native Apps, role-based access automation, and reusable lab environments.
Designed and delivered technical workshops on Snowpark ML, real-time data pipelines, streaming architectures, and cloud-native analytics workflows.

Education

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George Washington University

Doctor of Engineering in Artificial Intelligence & Machine Learning

Research-based doctoral work focused on advanced AI and machine learning methods, applied problem solving, and real-world AI/ML implementation.
Preparation for leading AI/ML initiatives across industry while building the research foundation for academic teaching and scholarship.