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:
Airbnb is a vision and mission driven company, and our Product Managers embody that mindset. Platform PMs imagine the ideal end state for our community first, work backwards from it, and deliver it in a scalable way. The AI Assistant team owns the agentic AI system that powers Airbnb's support experience for millions of guests and hosts. This is one of the highest-visibility applied-AI efforts at the company, and it sits at the intersection of large language models, platform thinking, and a genuinely two-sided marketplace.
The Difference You Will Make:
You will own the platform that determines how our AI Assistant reasons, retrieves, and responds: the layer that interprets each request and routes it, the knowledge and capabilities the assistant draws on, the actions it can take to actually resolve an issue, and the evaluation systems that keep it safe and accurate at scale.
You will own what a good outcome looks like for the user, and the criteria we measure it against, working through partners who own the underlying knowledge and the engineering implementation. This is a role where Product both directs technical work and does it themselves. You will diagnose architectural problems, author the artifacts that become production behavior, and help drive engineering and data science decisions alongside your key partners.
Support is high-stakes: people reach out when something has gone wrong, often with another party involved. You will be responsible for making those moments accurate, safe, and genuinely helpful, increasing how often the assistant fully and correctly resolves a request on its own while expanding coverage across more problem types and user touch points.
A Typical Day:
- 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.
- 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.
Your Expertise:
- 9+ years building technology products, with at least 5 in product management or a closely related technical role (engineering, data science, or applied research) from which you owned product direction.
- Direct experience shipping generative AI or ML products to production, ideally including retrieval-augmented generation, agentic or function-calling architectures, and evaluation systems.
- Hands-on technical depth. You read and debug prompts, understand ML and engineering constraints, and are comfortable personally authoring the artifacts that shape production behavior.
- Data fluency. You can work directly with production data, validate an analysis end to end, and know when a result looks wrong, whether or not you write the query by hand.
- Depth in LLM evaluation. You have designed, calibrated, or certified automated model-based evaluations, and can turn a vague quality signal into diagnostic, measurable components.
- A strong sense for great user experience, including how latency, tone, and trust shape an AI interaction.
- Comfort owning an ambiguous, cross-cutting mandate that spans several teams' focus areas, and the influence to drive alignment accordingly.
- A track record of scaling your impact through others: setting a clear bar, assigning owners, and holding them to it.
- Strong executive communication: can lead with the decision and the ask, and adjust the narrative to the audience.
- Radical thinking paired with strong execution: can envision a system meaningfully better than today and articulate the path to get there.
Your Location:
This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.
Our Commitment To Inclusion & Belonging:
Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.
We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: [email protected]. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process.
We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.
How We'll Take Care of You:
Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.
Skills Required
- 9+ years building technology products
- At least 5 years in product management or a closely related technical role such as engineering, data science, or applied research
- Experience owning product direction in a product management or closely related technical role
- Direct experience shipping generative AI or machine learning products to production
- Experience with retrieval-augmented generation, agentic architectures, or function-calling architectures
- Hands-on technical depth, including reading and debugging prompts and understanding machine learning and engineering constraints
- Ability to author artifacts that shape production behavior
- Ability to work directly with production data and validate analyses end to end
- Experience designing, calibrating, or certifying automated model-based evaluations
- Ability to translate quality signals into diagnostic, measurable components
- Strong understanding of user experience factors including latency, tone, and trust in AI interactions
- Experience owning ambiguous, cross-cutting initiatives spanning multiple teams
- Ability to influence partners and drive cross-functional alignment
- Track record of scaling impact through others by setting standards, assigning owners, and holding them accountable
- Strong executive communication skills
- Ability to envision improved systems and execute a path to deliver them
Airbnb Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Airbnb and has not been reviewed or approved by Airbnb.
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Fair & Transparent Compensation — Pay ranges and total compensation components are increasingly disclosed, and country-level pay practices avoid location-based cuts, which feedback suggests improves consistency and perceived fairness.
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Healthcare Strength — Comprehensive core health coverage for employees, mental health resources, and substantial dependent support are repeatedly highlighted as robust and a standout element of the package.
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Leave & Time Off Breadth — Generous PTO, a winter shutdown, sabbaticals, and paid volunteer time are described as extensive, with parental leave and phased return options reinforcing time-off flexibility.
Airbnb Insights
What We Do
Airbnb is a community based on connection and belonging—a community that was born in 2008 when two hosts welcomed three guests to their San Francisco home, and has since grown to 4 million hosts who have welcomed over 800 million guest arrivals to about 100,000 cities in almost every country and region across the globe. Hosts on Airbnb are everyday people who share their worlds to provide guests with the feeling of connection and being at home. At Airbnb, we believe that hosts, guests and the communities where we operate are all stakeholders we have a responsibility to serve, and that by serving them alongside our employees and investors, we will build an enduringly successful company.
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