
Hello! I Am Ross Taylor



Hello! I Am Ross Taylor
A Designer who
Designs the click
before the
click.
Because the best UX feels like it knew you'd be there — and great UI is the proof you arrived in style.
I'm a |
Currently, I'm a Principal UX/UI Designer atGLINT
A self-taught UX/UI designer, functioning in the industry for 24+ years now. I make meaningful and delightful digital products that create an equilibrium between user needs and business goals.
Work Experience
GLINT - Principal UX/UI Designer
GLINT is a native AI-powered software (agentic) development environment that enables issue-driven workflows, allowing developers to manage GitHub issues, code, and AI agents simultaneously.
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TDS Telecom - Senior UX/UI Designer
TDS Telecom (TDS®) delivers high-speed internet, TV entertainment, and phone services to a mix of small to mid-sized urban, suburban and rural communities.
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HealthEdge - Lead UX/UI Designer
HealthEdge, is a AI-Powered Healthcare Platform for payers connecting health plans, providers, and patients. It services over 115 health plans and 110 million covered members across the U.S..
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Aflac© - Lead UX/UI Designer (COE Team)
Aflac specializes in voluntary supplemental insurance. Based in Columbus, Georgia, it is a Fortune 500 company serving millions of policyholders in the U.S. and Japan.
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that values improving people's lives through accessible design
Featured Project
GLINT — Issue-Driven AI Development Environment
A native, AI-powered desktop IDE that puts GitHub issues, code, and AI agents in the same window. I led product design end-to-end — from positioning and information architecture to the live UI of Glint Assist, the in-editor AI partner. Issues, branches, the editor, and the assist panel are designed as one workflow, so developers can triage a ticket, ship the fix, and let AI close the loop without context-switching between five tools.
Featured Project
Aflac Leave Forecaster — Predictive AI for HR
An AI-assisted absence-prediction tool I designed for the Aflac COE team. The Forecaster pulls leave history, seasonality, and event signals to surface high-risk weeks 4–6 weeks out, so HR teams can plan staffing instead of reacting to it. Shipped at 50M+ policyholder scale: 92% prediction accuracy, ~45% reduction in admin overhead, and 75% faster benefits enrollment in the same release.