Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
Communication @ 6
Debugging @ 5
Distributed Systems @ 3
Java @ 5
LLM @ 3
Microservices @ 5
Observability @ 5
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
The Application Platform team builds application-level building blocks that enable Airbnb engineers and AI agents to ship product behavior safely and quickly without assembling or operating the underlying infrastructure.
The role focuses on critical services including dynamic configuration, distributed counting, asynchronous job processing systems, application gateways, and other high-scale, production-facing systems. Success requires a strong understanding of service-oriented architecture and system design, the ability to implement reliable, simple, and efficient solutions spanning multiple systems, and effective collaboration across teams.
Responsibilities
- Design and implement distributed systems and significant parts of production services.
- Implement core features in collaboration with other engineers.
- Develop rollout and testing plans and participate in the team’s on-call rotation.
- Maintain and debug existing systems, including fixing bugs, improving test coverage, optimizing performance, contributing to production excellence, adding features, conducting code reviews, and creating observability dashboards.
- Provide technical support to engineers and developers by answering questions, debugging code, and troubleshooting problems.
- Partner with stakeholders to understand feature requests, design solutions, and deliver them as expected.
- Stay current with emerging trends and technologies, including identifying AI technologies that can improve the future state of the systems.
- Collaborate with engineers across Airbnb, external teams, partners, and stakeholders on company-wide initiatives.
Requirements
- Bachelor’s and/or Master’s degree, preferably in Computer Science, or equivalent experience.
- 3+ years of industry experience.
- Experience working on distributed systems and evaluating technical trade-offs.
- Proficiency in Java, microservices, observability systems, and debugging distributed and multithreaded systems.
- Willingness to engage in an AI-first engineering approach using LLM-powered agents to generate and iterate on code while focusing on problem-solving, system design, and quality oversight.
- Strong technical communication skills, including writing design documents, presenting in design reviews, and writing effective post-mortems.
- Proactive communication and collaboration skills across teams through code reviews and architecture discussions.
- Motivation to contribute to a positive and inclusive team culture.
- Interest in joining an impactful infrastructure team.
Benefits
The role may be eligible for a bonus, equity, benefits, and Employee Travel Credits. Airbnb also provides reasonable accommodations throughout the recruitment process for applicants with disabilities.
Compensation
The base pay range is $162,000–$190,000 USD per year. Actual base pay depends on factors including training, transferable skills, work experience, business needs, and market demands.