Staff Software Engineer, Payments Transaction Risk

Airbnb was born in 2007 when two Hosts welcomed three guests to their San Francisco home, and has since grown to over 4 million Hosts who have welcomed more than 1 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’s mission is to create a world where anyone can belong anywhere. The Airbnb Payments Risk team supports this mission by protecting Airbnb’s ecosystem from fraudulent transactions while ensuring a seamless payment experience for legitimate users.

The Payments Risk team focuses on detecting and mitigating fraud during payment-related steps, such as checkout, refunds, payouts, claims, and instrument creation. The team’s detection systems combine Machine Learning models and rule-based systems to identify fraudulent activities across homes bookings, experiences, and claims and resolutions. Our mitigation systems ensure good users operate smoothly while introducing targeted frictions for suspicious activities.

The Difference You Will Make:

As a Staff Software Engineer on the Payments Risk team, you will play a critical role in designing and building systems to combat payments-related fraud, maintain platform integrity, and provide a secure, reliable user experience. Your work will directly contribute to making Airbnb’s global community safer and more trustworthy.

As a Staff Engineer, you will:

• Design and lead the implementation of complex, scalable systems to detect and mitigate payment fraud effectively.
• Collaborate across teams, aligning architecture, dependencies, and shared goals with stakeholders in Product, Machine Learning, Finance, and Operations.
• Provide technical leadership, making high-impact decisions balancing technical trade-offs and business objectives.
• Mentor engineers at various levels, fostering technical growth and a culture of excellence within the team.
• Drive the technical roadmap, aligning immediate projects with long-term organizational goals and addressing technical debt thoughtfully.

A Typical Day:

• Lead the architecture and design of a scalable, distributed system for fraud detection and mitigation.
• Collaborate with Machine Learning engineers to integrate predictive models into real-time detection pipelines.
• Partner with Product and Design teams to improve anomaly detection workflows and enhance user verification processes.
• Work with Engineering teams across Airbnb to define and implement shared standards for fraud detection and mitigation systems.
• Mentor team members through design reviews, code walkthroughs, and knowledge-sharing sessions.

Why You’ll Love This Role

• Impact: Your work will protect Airbnb’s community from fraud, ensuring a safe and trusted platform for millions of users worldwide.
• Growth: You’ll work on complex technical challenges, mentor talented engineers, and contribute to the evolution of Airbnb’s Payments Risk systems.
• Collaboration: Join a passionate, diverse team and collaborate across disciplines to solve meaningful problems.

Your Expertise:

• 9+ years of software development experience, with at least 5 years in payments or financial technology domains.
• Strong understanding of payment fraud detection, chargebacks, and global payment processing flows (e.g., credit cards, bank transfers, e-wallets).
• Proven experience designing and deploying large-scale distributed systems with a focus on scalability, reliability, and maintainability.
• Proficiency in Java, Kotlin, and/or Scala, with familiarity in asynchronous programming models (e.g., events, callbacks, promises).
• Expertise in designing APIs, building RESTful services, and integrating message queuing and data streaming frameworks.
• Deep experience with relational databases, caching solutions, and service-oriented architecture.
• Strong leadership and communication skills, with experience mentoring engineers and leading cross-functional initiatives.
• Nice-to-Have Skills include:
  • Experience with Machine Learning applications in fraud detection.
  • Familiarity with workflow frameworks and anomaly detection systems.
  • Background in agile development and continuous delivery pipelines.

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.