Lead - Conversational Interfaces

At , data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make.

Through our products, partners and people, we make it easier for everyone to experience the world!

The Lead GenAI Conversational Interfaces drives the continuous improvement and optimization of a defined scope within the Digital Partner Ecosystem's conversational AI product portfolio (currently covering search experiences, agents as well as the underlying RAG infrastructure).

This role owns the performance, quality, and evolution of partner-facing conversational interfaces through content and related infrastructure enhancements - including knowledge architecture optimization, skills and evaluation framework management, and information retrieval systems.

Grounded in partner feedback and conversation data analysis, they deliver measurable improvements in partner self-service adoption, answer quality, and support efficiency while maintaining compliance with content governance and safety standards.

Operating within a collaborative framework, this role partners closely with fellow leads across distinct areas of the GenAI portfolio, Partner Support, Partner Hub backend and infrastructure, UX, as well as engineering, machine learning, data science, content, and legal/compliance teams. Clear scope definition and cross-functional alignment ensure efficient collaboration and avoid duplication across the GenAI product portfolio.

Drive the impact of partner-facing conversational AI on the Hub (Smart Search, Support Agent) through content and related infrastructure enhancements — including knowledge architecture optimization, skills and evaluation framework management, and information retrieval improvements. Focus on channel performance, partner experience quality, and content governance — aligned with department priorities and the innovations roadmap.

Track and improve conversational AI KPIs — answer quality, task completion, self-service adoption, contact reduction, and partner satisfaction — identifying tactics/opportunities by diving into partner conversations, feedback, and operational data.

Use human-in-the-loop evaluation and in-product measurement to identify recurring issues, own the continuous feedback-to-improvement loop, and discover insights and opportunities for quality and operational health; not relying solely on automated judge scores.

Own and prioritise the conversational AI channel backlog — including quality improvements, content guidelines work, measurement implementation, and partner experience enhancements — based on partner needs, business impact, technical feasibility, and compliance requirements. Align across the team on priorities across shared resources.

Monitor live sessions and partner feedback for recurring pain points or quality gaps; resolve directly within own scope, and pass signals with innovation or roadmap implications to cross-functional leads and other key stakeholders.

Represent the partner perspective decisions — incorporating partner feedback, session data, and content quality signals into solution design, and advocating for experiences with customer centricity.

Coordinate and challenge internal and external contributors across product, engineering, data science, content, and vendor teams with clear requirements, priorities, and quality…