Conversational Interfaces Lead

Booking.com; Amsterdam; Hybrid; EUR 110,000 - 160,000; Full time

Benefits offered by this job

Health insurance

Headspace access

Employee assistance program

Life insurance

Pension plan

Annual leave

Remote work support

Job summary

Booking.com seeks a seasoned professional to lead GenAI conversational interfaces within the Digital Partner Ecosystem. You will drive improvements in content, retrieval systems, and evaluation frameworks, aligning with partner feedback and safety standards.

You will collaborate across product, engineering, data science, content, and compliance to deliver measurable gains in partner self-service and support efficiency, while maintaining governance and quality standards.

Qualifications

• Proven experience in Product Operations, Product Management, or Technical Program Management
• Experience driving continuous improvement and performance optimization of Conversational AI products in production
• Hands-on experience with prompts, dialogue flows, and AI-served content at scale
• Ability to design and interpret AI quality evaluations, including human-in-the-loop frameworks
• Strong stakeholder communication and cross-functional collaboration skills

Responsibilities

• Drive continuous improvement of partner-facing conversational interfaces within the Digital Partner Ecosystem portfolio
• Own performance, quality, and evolution of content and knowledge architecture
• Track and improve KPIs: answer quality, self-service adoption, contact reduction, partner satisfaction
• Coordinate cross-functional teams (product, engineering, data science, content, legal/compliance) to define scope and priorities
• Represent partner perspective and translate feedback into actionable design and roadmap decisions
• Manage backlog and governance related to content quality and retrieval systems
• Monitor live sessions and partner feedback to identify issues and opportunities for improvement

Skills

Product Operations

Product Management

Technical Program Management

Data-Driven Evaluation

Content & Prompt Execution

Project Management

Stakeholder Communication

Technical Literacy

Human-in-the-Loop Evaluation

Knowledge Architecture

Job description

• 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 expectations

Benefits

• Health insurance
• Free access to Headspace for you and your loved ones
• Global Employee Assistance Program
• Meditation and Breastfeeding rooms at the office
• Booking Cares - 2 days per year to volunteer and learn
• Life insurance
• Disability insurance
• Pension plan
• Annual paid time off
• Parental leave - 22 weeks
• Grandparent leave - 10 days
• Care leave - 10 days
• Bereavement leave - up to 4 weeks
• Anniversary leave
• Working from Home Furniture and Ergonomic Support
• Working from Abroad - up to 20 days per year
• Discounts & Wallet credits to spend on our products
• Upgrade to Booking.com Genius Level 3
• Friends & Family Booking.com discount vouchers
• Free access to online learning platforms
• Development and mentorship programs to support career growth
• Access to trainings and workshops
• Team development opportunities
• Local discount programs
• Game rooms in offices
• On-site meals, coffee and snacks including vegan options

Business Acumen - Frames day-to-day work in terms of answer quality, self-service rates, and contact reduction; connects fixes and improvements to DPE commercial metrics and CS outcomesAI Operations & Continuous Improvement - Proven track record of running the day-to-day operations of a live AI/conversational product, driving continuous quality and content improvements based on real usage and partner feedbackProven experience (4+ years) in Product Operations, Product Management, or Technical Program Management, with proven focus on driving continuous improvement and performance optimization of Conversational AI products in productionContent & Prompt Execution - Hands-on experience writing and iterating on prompts, dialogue flows, and AI-served content at scale; understands how content and prompt changes affect AI output and can execute improvements directly, not just define standards for othersProject Management — Methodical in breaking down complex cross-functional work and delivering against timelines independentlyData-Driven Evaluation — Comfortable designing and interpreting AI quality evaluations, including human-in-the-loop frameworks, session analysis, and in-product measurement — not reliant solely on automated judge scoresContent & Conversational Governance — Understands how content quality and guidelines affect AI output; experience working with content teams to define and maintain standards for AI-served or AI-generated content at scaleStakeholder Communication — Bridges technical and non-technical audiences; experienced in positioning AI work internally and translating complex technical concepts into clear business value propositionsTechnical Literacy — Understands knowledge architecture, retrieval systems, skills frameworks, evaluation methodologies, and GenAI infrastructure (RAG, LLM evaluation, model updates) well enough to challenge and prioritize technical decisions and scope boundaries without owning the underlying infrastructure implementation