The opportunity
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…
What you'll do
Set the product direction for how the assistant reasons and responds, and: paint a multi-quarter vision with the customer at the center; align that vision with senior leaders and cross-functional partners.
Work fluently with production data. Explore the data directly, use modern AI: tools and coding agents to move fast, validate an analysis, and dig in yourself to tell when a result doesn't look right.
Build new capabilities end to end, from spotting the need through the: hands-on work that makes the behavior real and gets it calibrated with human input.
Decide what a correct, complete resolution looks like for each kind of user: problem, and get engineering, policy, and knowledge partners aligned around that definition.
Define what success means in measurable terms: how often issues get fully resolved, how accurate and safe the answers are, and the bar that a change needs to clear in order to launch.
Own launch readiness for major model and platform changes, balancing speed to: learn against the safety and risk work that has to happen before anything scales.
What they're looking for
- Diagnose why a complex AI system is failing, and judge where the fix actually belongs.
- Own the evaluation strategy: LLM-based evaluators (LLM-as-judge), offline and live-traffic evaluation, calibration and certification, and the tooling that lets non-engineers safely improve the assistant.
- Bring teams with different perspectives to a shared answer, set agreements: with partners early, and push for a single source of truth across the product.
- Present to leadership regularly, leading with the decision, the tradeoffs,: and the ask, and tailoring the narrative to what the audience cares about.
