Build AI-driven test infrastructure and CI/CD tooling for Airbnb's Android codebase at scale

This role sits at the intersection of Mobile Infrastructure, Developer Experience, and Applied AI - building the testing frameworks and LLM-powered tooling that keep thousands of engineers shipping confidently. The interview should probe hands-on Kotlin/Android infrastructure depth plus applied-AI tooling instincts, not app-feature work.

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What this interview tests

Kotlin and Android SDK depth, including Gradle build lifecycle
Building/maintaining test automation frameworks at scale (Espresso, Compose Test)
Applying LLMs to CI/CD: smart test orchestration, test generation, autonomous test discovery
Influencing architecture reviews for modularity and testability
Operating high-availability (24x7) developer infrastructure
Navigating a large, complex, ambiguous mobile codebase

Common question themes

Describe a test automation framework you built or extended at scale - what broke and how did you fix it

How would you design an LLM-based system for autonomous test discovery or smart test orchestration

Tell me about a design review where you pushed back on an architecture for testability reasons

How do you identify and resolve systemic bottlenecks in a large team's development lifecycle

Walk through a CI/CD pipeline you improved and the impact on developer velocity

How do you ensure high availability of shared testing infrastructure that hundreds of engineers depend on

How candidates describe it

Real Android Software Engineer interview stories — retold from candidates' public write-ups, with sources.

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Interviewed January 2023 · Not specified

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