The posting, in Airbnb's own words
archived Oct 27, 2026Airbnb 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
The Experimentation team's mission is to provide an insightful, reliable and easy to use experimentation platform (A/B testing and feature rollout) for customers across the company. Thousands of experiments run on our platform each year. Our team is multidisciplinary, owning UIs for setting up and analyzing experiments, data pipelines and libraries for calculating results, and clients for assignment and delivery. You will work closely with design and data science partners and with the engineers and analysts across the company who use our tools every day.
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The Difference You Will Make
You will co-own the web application where teams set up, manage and analyze experiments and feature configuration, and the AI-assisted workflows that are becoming part of how experiments are designed, validated and read out. You will build features end to end, from the React/TypeScript interface through Python APIs to the data layer, and make our tools intuitive and trustworthy for users with a wide range of statistical backgrounds. Success looks like features that measurably speed up experiment setup and readout, and AI-enabled tools that people adopt because they are reliable.
A Typical Day
Develop new features across the client (React/TypeScript), APIs (Python/GraphQL) and database, and own them from design through on-call. Work with design and key customers to shape intuitive experiences, including how to visualize experiment results so users with minimal statistical training draw good conclusions. Build AI-enabled workflows for our users, such as agent tools and skills that help create, validate and analyze experiments, and the interface around them, with evaluations that keep quality high. Use AI-assisted development to move faster, and help the team set good practice for it. Work with data science partners to bring new methodology into the product. Participate in experiment reviews to understand how customers use the platform and where it falls short.