Senior Software Engineer, Infrastructure
About the role
The Community You Will Join
The Quality Platform team is at the heart of Airbnb's mission to deliver a seamless, high-quality experience for millions of hosts and guests. We don't just find bugs — we build the systems that prevent them.
Our team sits at the intersection of Quality Engineering, Infrastructure, and Applied AI. We are evolving how software quality is built by integrating LLMs, intelligent automation, and data-driven systems into the testing lifecycle. You will join a high-impact group of engineers focused on building AI-powered quality systems that scale across one of the world's most complex codebases.
The Difference You Will Make
As a Senior Software Engineer, you will play a key role in building and evolving AI-native quality workflows across Airbnb. You will design systems that apply AI directly to the testing lifecycle, helping developers and quality engineers build, validate, and ship high-quality software at scale.
In this role, you will:
- Build AI Agents for the Testing Lifecycle: Design and implement AI agents that support developers and quality engineers across the testing lifecycle — from test case generation and evolution to automation and maintaining test coverage as the codebase changes.
- Advance AI-Native Quality: Move beyond traditional automation by building systems that continuously adapt test coverage based on code changes and system behavior.
- Improve Developer and QE Productivity: Identify bottlenecks in testing and CI/CD workflows, and solve them through intelligent automation that reduces manual effort and accelerates feedback loops.
- Integrate AI into Engineering Workflows: Embed AI capabilities into real development environments, enabling both developers and quality engineers to receive contextual, actionable insights during development and testing.
A Typical Day
- Hands-on Development: Build end-to-end systems and tools (TypeScript, Swift, Kotlin, Java, Python) that will power Airbnb's AI quality platform. This includes services, developer tooling, and UI surfaces that integrate AI into testing frameworks/infrastructure, CI/CD pipelines, and everyday developer workflows.
- Applied AI: Develop AI-assisted capabilities such as context-aware agentic E2E validation on pull requests, agentic execution of business-critical flows as quality gates, agentic surface discovery and exploratory testing, and systems for test case generation, and coverage maintenance.
- System Design: Participate in the design of scalable AI-driven systems operating within large-scale engineering environments.
- Cross-Functional Collaboration: Work closely with Mobile, Infrastructure, Product Engineering, and Quality Engineering teams to integrate AI into real-world development workflows.
- Experimentation & Iteration: Explore approaches such as prompt engineering and RAG (Retrieval-Augmented Generation) to improve system effectiveness and adaptability.
- Mentorship: Provide technical guidance and help raise the bar for applying AI in engineering systems across the team.