Product Manager

Who you are

• Proven track record of shipping AI-native products in production, not prototypes or side-projects. You've built products where AI is the core, not a feature
• Strong communication and stakeholder management across all levels, from engineering to leadership teams. You simplify complexity without losing substance
• Experience with spec-driven product development: writing clear, unambiguous specifications with defined inputs, outputs, decision logic, and edge cases
• Solid technical understanding of AI/ML systems, LLMs, agent orchestration, and enterprise data platforms. You make product decisions informed by how the technology actually works
• Demonstrated experience in finance or fintech platforms. You understand ERP systems, reconciliation, forecasting cycles, and compliance requirements (SOx, audit trails)
• Experience designing platform and governance layers — agent registries, escalation frameworks, monitoring, and the transition from point-solutions to reusable infrastructure
• Familiarity with agile delivery, but comfortable operating in ambiguity: this is zero-to-one work, not backlog management

What the job involves

• Booking is building two AI-native products for Finance: Natural Intelligence (a natural language interface over governed financial data) and Autonomous Finance (AI agents that autonomously execute operational finance workflows, with a human in/on the loop processes)
• We're looking for a Product Manager whose initial focus will be Natural Intelligence: owning the end-to-end experience of how AI systems interact with enterprise finance data
• The vision is to have zero distance between a question and an answer
• You'll be the primary author of what gets built, translating complex finance domain problems into high-fidelity specifications that engineering and AI systems can execute against
• You'll define how the system should interpret financial questions, what data it can access, how answers are governed and presented, and what "right" looks like across different user personas, from a CFO asking about cash position to an FP&A lead investigating variance drivers
• The quality of what you specify determines the quality of what gets built
• This means you'll need a strong intuition for data
• How financial data is structured, how reporting layers work, what makes a metric trustworthy, and how to bridge the gap between raw data systems and the natural-language experience users expect
• You'll work closely with data engineering and analytics teams to define the semantic layer, govern data access, and ensure answers are accurate, auditable, and contextual
• Own the strategy and roadmap for Natural Intelligence and Autonomous Finance, ensuring alignment with Finance leadership priorities and Booking Holdings' AI strategy
• Define Product success metrics that measure real operational outcomes and be accountable for outcomes, not output
• Drive discovery as the highest-value activity: spend significant time with finance SMEs understanding the real process, the real data, and the real edge cases before anything gets built
• Design individual agents and NLQ capabilities now while identifying what becomes reusable platform infrastructure (escalation framework, shadow mode pattern, monitoring, agent registry, governance model)
• Author high-fidelity intent artefacts: specifications precise enough for AI agents and engineering teams to execute against
• Co-author with engineering: iterate on specs with Data Engineers and Engineers until the solution is right
• Partner with stakeholders across Finance (CFO office, Operations, FP&A, O2C, Procurement), Central Tech (ML Platform), and Data Engineering to understand needs, prioritise, and manage expectations
• Translate complex finance domain challenges into clear product requirements, leveraging AI and automation to scale human productivity across finance
• Communicate progress, risks, and roadmaps to senior stakeholders and cross-functional teams with clarity and confidence
• Collaborate with other product teams across Booking to align on shared infrastructure, platform decisions, and execution priorities
• Leverage data analytics and experimentation to inform product decisions: test agent accuracy, evaluate user adoption patterns, and continuously optimize

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