Staff Product Manager, AI Personalization

Airbnb is a global company that connects hosts and guests, and they are seeking a visionary Staff Product Manager to lead the product strategy and execution for AI Personalization in their customer support ecosystem. This role involves owning the full stack of personalization, enhancing AI understanding of users, and building a platform that delivers tailored support experiences.

Responsibilities:

• Contribute towards the long-term vision for building 10-star, personalized community support, building a platform where our AI understands each guest and host the way their best human advocate would, and responds accordingly
• Partner with data science, ML, and operations to identify new high-signal personalization signals to serve user needs
• Own the product roadmap across ML models, signals, schemas, and prompt optimization to ensure the right information reaches the model in the most effective form
• Drive personalization experiment design and measurement: define KPIs (self-solve rate, personalization coverage, citation accuracy), lead experiment design, and translate results into clear product decisions
• Collaborate with ML engineers to shape requirements for accuracy, latency, and scalability improvements
• Scale personalization infrastructure across Airbnb's AI surfaces, ensuring the platform is extensible enough to serve each modality's unique needs
• Build a framework for continuous improvement: define how the team identifies personalization failures, prioritizes fixes, and systematically closes the gap between AI and human agent performance
• Collaborate across engineering, ML, design, data science, and policy to build consensus on prioritization, drive cross-functional alignment, and ship with rigor from concept to production

Requirements:

• 9+ years of industry experience with a BS/Masters OR 6+ years with a PhD, with deep expertise in AI/ML-powered platforms at consumer scale
• Strong working knowledge of personalization systems, contextual data retrieval, and LLM architectures - you can engage credibly with ML engineers on topics like RAG, retrieval optimization, and context engineering tradeoffs
• Track record of building and shipping foundational platform products that power multiple downstream experiences and surfaces
• Experience designing and interpreting A/B experiments and online experiment frameworks; ability to own end-to-end metrics strategy for complex AI systems
• Strong capacity to synthesize ambiguous signals into clear, prioritized product decisions
• Proven cross-functional leadership: able to align ML, engineering, data science, design, and operations teams around a shared vision
• Experience shipping consumer-facing AI products with personalization at the core
• Sharp product intuition for when AI automation should give way to human judgment, and how to design systems that make that transition seamless
• Ability to work at multiple levels of abstraction - from the architecture of a retrieval system to the experience of a guest trying to resolve a cancellation dispute