Airbnb is hiring a

Senior Software Engineer, Trust - Financial Fraud

San Francisco, United States

What is Trust at Airbnb?

Airbnb is built on trust. Over two million people stay on Airbnb every night and the Trust Engineering team keeps our hosts and guests safe and supported throughout the entire Airbnb experience. We’re creating new relationships & placing people in vulnerable situations. Therefore trust is the fundamental currency of Airbnb. The Trust team builds trust by creating safety at every stage of the journey from the moment the user visits Airbnb. We set the standards & expectations for our community, keep bad actors out and and build products for good users to thrive without getting caught in the net.

We constantly work to fight against online fraud (through compromised accounts, spam and scam in messages, fake inventory, etc.) as well as preventing offline incidents (theft, property damage, personal safety, etc.). We work on onboarding and making accounts secure, and think about complex topics like identity, reputation, privacy, and anti-discrimination to ensure that every interaction with Airbnb helps build trust in us and our community. Trust Engineering is responsible for the technology vision and development of a complex stack that runs on every key interaction on the platform.

About the Financial Fraud Team on Trust

The Financial fraud team is responsible for protecting our platform and community from financial fraud losses. This includes preventing abuse of our host insurance policy, misuse and stealing of gift cards and coupons, and combating compromised account payouts and fraudulent booking adjustments. This team is tasked with building and maintaining the product features, services, agent tooling, and ML models that power these defenses.

What is a Software Engineer on the Financial Fraud team?

As a Software Engineer on the Financial Fraud team, you will be working with data scientists, designers, product managers, and customer service operations to innovate new ways we can stop bad actors in the ever evolving financial fraud landscape. 

On this team, you must have the curiosity to dig deep into various end to end systems in order to understand how and where the fraud occurs. Your curiosity will be rewarded with finding projects that have outsized impacts on decreasing fraud losses while increasing revenue. Your contributions will take a variety of shapes:

  • Building and maintaining a long-term technology stack with well defined APIs that is service-oriented, modular, granular, observable, and efficient
  • Improving the overall quality and observability of our defenses.
  • Building out new detection and mitigation strategies that will make it easier for good users and harder for bad actors.
  • Optimizing operations work flows and remediation queues to reduce company costs.
  • Employing machine learning models to prevent fraud from occurring.
  • Working with cross-functional teams with design, product, data science, and research partners to drive engineering decisions and influence outcomes

Projects we are working on:

  • Working towards building out a world class financial fraud prevention platform with configurable suite of user experiences, machine learning models, and agent tooling that combat financial fraud, and other types of abuse on the platform, while building trust between hosts and their guests
  • Maintaining and optimizing our current defenses, and increasing observability to operations to increase the understanding of how fraud occurs on our platform.

Requirements:

  • 5+ years of industry experience on large scale systems
  • Passion for building user-facing products or large backend systems.
  • Experience in any of the following: Ruby/Ruby on Rails, Java, JavaScript, Python, Scala
  • Ability to write high performance production quality code
  • Exposure to architectural patterns of large, high-scale web applications, such as well-designed APIs, high volume data pipelines, and efficient algorithms.
  • Experience or desire to work collaboratively in cross-functional teams with design, product, data science, and research partners.
  • Ability to effectively communicate with non-technical stakeholders such as legal and operations.
  • Machine learning experience optional. Fraud experience is a bonus and not a must.

Benefits:

  • Stock
  • Competitive salaries
  • Quarterly employee travel coupon
  • Paid time off
  • Medical, dental, & vision insurance
  • Life insurance and disability benefits
  • Fitness discounts
  • 401K
  • Flexible Spending Accounts
  • Apple equipment
  • Commuter subsidies
  • Community involvement (4 hours per month to give back to the community)
  • Company sponsored tech talks and happy hours
  • Breakfast, lunch, and dinner
  • Much more…

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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