Staff Software Engineer, Guest Displays & Platforms

Airbnb, a pioneering force in the travel and hospitality industry since 2007, is seeking a Staff Software Engineer for their Guest Displays & Platforms team. This role sits at the intersection of critical business functions, managing pricing and availability across all product surfaces and the main product details page (PDP). The position offers an opportunity to shape the core user journey for Airbnb guests, working with large-scale systems that impact millions of users worldwide.

The role demands a unique blend of technical expertise and leadership skills, requiring the successful candidate to lead the development of major subsystems while collaborating across multiple teams including Search, Checkout, Reservations, and Payments. As a Staff Engineer, you'll be responsible for establishing technical vision and delivering scalable solutions that maintain high availability and efficiency.

The position offers competitive compensation ranging from $204,000 to $255,000 USD, along with the flexibility of remote work within the United States. This is an excellent opportunity for experienced engineers who want to make a significant impact at a company that has facilitated over 2 billion guest arrivals globally.

The ideal candidate will bring 10+ years of relevant software development experience, with deep expertise in both backend systems and front-end development. You'll be expected to mentor other engineers, drive technical quality, and balance short-term business needs with long-term technical excellence. The role requires someone who can think strategically while maintaining a hands-on approach to solving complex technical challenges.

Working at Airbnb means joining a company committed to inclusion and belonging, where diverse ideas are valued and innovation is constantly driven by real-world user needs. The company's culture emphasizes collaboration, technical excellence, and a user-first mindset, making it an ideal environment for engineers who want to work on meaningful problems at scale.