How UX and AI teamed up to transform recruiting at Amazon

I led UX research and product design to evolve an AI chatbot used by Amazon recruiters, addressing knowledge gaps, building features to support learning through human collaboration, and ultimately improving engagement, task success, and productivity. My work helped recruiters save time, share knowledge securely, and attract top talent, while reducing reliance on costly third-party tools.

35%

Improved onboarding process

25%

Increase in user retention

84%

Increase in time spent on website

3D Render

Context & Background: Scaling Knowledge Sharing Across 5,000+ Recruiters

Amazon employs 5,000+ recruiters drowning in a dozen disconnected tools – from Slack to internal Wikis and emails. Manual knowledge hunting wasted hours daily.

Amazon employs thousands of recruiters across teams and time zones—each juggling tools like email, Slack, internal wikis, and Quip to find or share critical information. Fragmentation led to inefficiencies and lost knowledge, especially when switching contexts or onboarding new recruiters.

To help, Amazon launched an internal beta chatbot called TILT, powered by Amazon Kendra. TILT uses natural language processing to answer recruiter questions and surface talent data—minimizing the need for manual searches.

Users & Stakeholders

The Heroes: Recruiters battling chaotic hiring surges.

Their Burden:
Juggling 14+ platforms to find answers
Risking resume leaks via unauthorized tools
Reinventing solutions for identical questions

Problem / Opportunity & Goals

Problem: TILT was only as smart as the knowledge it indexed—which meant it often couldn’t help with specific or uncommon queries. TILT’s AI could only answer 30% of recruiter questions – leaving critical gaps in live hiring scenarios. Recruiters needed answers, fast. Many turned to Slack, where informal Q&A, resume sharing, and discussions happened—but on an external tool with privacy, security, and cost concerns.

We saw an opportunity:

Could we enhance TILT with human-powered knowledge sharing—making it both more helpful now and smarter over time? We could turn unanswered questions into crowd-sourced wins while training the AI.

Success Metric(s):
Knowledge Coverage: Resolve 90% of recruiter queries
Improve task completion rates with TILT
Increase user trust and engagement with AI
Security: Reduce Slack reliance and resume sharing outside internal tools
Create a scalable, secure system for recruiter knowledge exchange
Cost: Replace $1M+ Slack dependency

Challenges

Stakeholder Skepticism: Engineering saw community features as "scope creep"
Tool Fragmentation: Recruiters refused another platform
Compliance Nightmares: Sharing candidate data internally required legal firewalls

Team, Role, & Responsibilities

I joined as a UI/UX designer shortly after the chatbot beta launched, embedded on a cross-functional team that grew from 7 to 14. My responsibilities included:
Leading research to identify user pain points and opportunities
Partnering with data engineering on discovery and validation
Designing core features: chat interfaces, feedback loops, human Q&A
Contributing components to AWS’s design system
Supporting handoff and quality assurance with engineering

Collaboration & Alignment: Cross-team alignment was essential. I worked closely with PMs, AI researchers, engineering, and recruiting leaders to define success and build trust. A key part of my role was navigating competing priorities—balancing chatbot limitations, security concerns, and recruiter urgency—to co-create solutions that worked for everyone.

Stack

Stack

Stack

“ With our new visual branding and language in place, the new Shopify brand clearly captures the essence of our current and target customer base, our employees, and our values. ”

Tobias Lütke

CEO, Co-founder | Shopify

Conclusion

The modernization of the subscription management platform successfully addressed the core usability issues and improved the overall user experience. By focusing on simplifying the interface and optimizing workflows, we were able to create a more efficient and enjoyable platform for users. The significant improvements in user engagement, satisfaction, and subscription rates underscore the importance of user-centric design in achieving business success.