Amazon AI Life Sciences

I led UX across the AI Life Sciences space, including our bioinformatics capabilities, Bio Discovery, and an AI-based drug discovery application for bench scientists, along with a product to streamline clinical trials. Across all three, my mandate was the same: make advanced AI usable, auditable, and trustworthy in real healthcare and life-science environments.

The challenges were different by product but shared a common pattern: fragmented systems, heavy cognitive load, and low tolerance for ambiguity. In Bioinformatics, teams struggled to interpret complex outputs across disciplines. In Bio Discovery, clinicians needed to understand why the model made a recommendation before they could trust it in diagnostic flow. In Trial Craft, cross-functional teams needed protocol and cohort decisions to be transparent, not buried in disconnected tools. The risk was not just friction; it was slower research, delayed decisions, and reduced confidence in AI-assisted workflows.

To move faster, our team vibe-coded an end-to-end product experience and built into the UI APIs to ensure the outcomes matched the design intent. This required reworking our team's design and handoff processes, building a new design system to support native AI experiences, pushing to invest in new research methodologies, and creating collaborative tools so designers could operate efficiently.