Product Designer

14

Years Experience

5+

Industries

AI Property Descriptions

Keller Williams · Proprietary real estate platform · Senior Product Designer · Sole designer, end-to-end

Real estate agents often face friction when drafting compelling, professional listing descriptions for diverse properties. The objective was to design a tool that leverages AI to generate high quality copy while ensuring the experience remained accessible for both first time users and sophisticated experts.

Objective

• AI tool to help agents draft professional listing copy

• Accessible to both first-time and expert users

Collaboration

• Group labs and agent interviews across market centers

• Partnered with ML engineers and PMs on confidence signals

• Led critiques to align the org on AI component standards

Constraint

• Agents reject black-box AI; transparency required

• Two-week sprints with hard scope limits

• WCAG AA non-negotiable

Result

• Inline AI-rationale patterns adopted by two additional KW products

Multiple
Breakpoints

AI
Enabled

Objective

• Rebuilt the Associate Production view used by Market Center Leaders and Tech Trainers to coach real estate agents

• Turned a static report into a coaching tool that surfaces decisions in under 15 seconds

• Designed Command's first generative AI surface inside the same tab

Constraint

• Legacy view showed totals but no trajectory, hiding at-risk agents

• Addition of AI in a coaching tool

• Responsive breakpoints, error, empty, and loading states

Collaboration

• Designed three iterations based on feedback and synthesis pass with Market Center Leaders

• Wrote spec definitions and error-state microcopy to align engineering, QA, and future designers

• Partnered with ML and PM to define AI disclaimers, feedback taxonomy, and trust patterns

Result

• Removed need for users to have a separate tool or subscription

• Designed AI-Powered Insights with structured feedback loops that regenerate output in place

• Instrumented for engagement time, AI interaction rate, and feedback-signal quality post-launch

Web App
Native App

B2B+B2C
Dual Platform

Collaboration

• Partnered with 3 designers, 35 engineers, 4 PMs, and 1 PMM

• Co-led digital whiteboard sessions with PM to define vendor flows end-to-end

• Designed onboarding, dashboard, leads, jobs, service area, invoicing, and chat workflows

Result

• Secured $16M in funding from the proof-of-concept prototype

• Unlocked projected $1.5B annual revenue stream (15% cut of KW's $10B vendor spend)

• Scaled the project to the full KWX team and offshore engineering for MVP

At Keller Williams I led design for B2B and B2C products: AI-powered listings tools, dashboards, and a multi-sided home services platform. I own the full process: requirements gathering, flows, prototypes, usability testing, and dev-ready handoff.

I hold a Top 10% Distinction in AI for Designers from IxDF. Competencies include prompt engineering, mitigating algorithmic bias, and designing for responsible AI. I apply these in production — not just in theory.

Files are versioned. Layers are named. Figma components are documented. Engineers don’t need to ask twice. I attend Axe-con by Deque annually — accessibility is baked into my process, not bolted on at the end.

Austin, TX | Remote-Friendly