AI Engineer, Community Support Engineering
Posted May 24, 2026
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join:
Providing world class customer service for our community of guests and hosts is a critical mission for Airbnb. This area has unprecedented scale and complexity. In no other domain does the efficiency and reliability of customer service technology translate directly into a competitive advantage, brand loyalty, and the business's bottom line. The Integrated Knowledge Management team, part of Airbnb’s Community Support Engineering, is foundational to creating the best customer service experience for our community of hosts and guests. The Integrated Knowledge Management team is responsible for building robust and scalable platforms that enable Airbnb’s content and knowledge to be leveraged across internal and external users, and to serve as the authoritative knowledge source for AI-powered applications and support surfaces. The Difference You Will Make:
As an AI Engineer on the Integrated Knowledge Management team, you will help build out our next-generation Retrieval-Augmented Generation (RAG) platform and AI-powered support surfaces such as the Help Center. You will be deeply involved in building highly available and scalable services in close collaboration with engineering, ML/AI, product, content, data science and operations teams to meet the ever-evolving needs of Airbnb’s Community Support Engineering group. Many problems exist in this domain including expanding our RAG systems to support new knowledge and solution sources, building the capabilities required for Airbnb’s expanding suite of AI-powered contextual in-product support applications, and implementing ways to improve velocity around experimentation and evaluation.