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# Software Developer - Mobile

- **Company:** Adobe Systems
- **Location:** San Jose, CA, United States
- **Experience:** Experienced
- **Salary:** $177,900.0 - $257,550.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Multitier Architecture, Artificial Intelligence, Apple IOS, App Store (IOS), Automation of Tests, Mobile Application Development, Cloud Computing, Continuous Integration, Software Debugging, Memory Management, Model View ViewModel, TypeScript, Web Applications, Uikit, Multithreading, Swiftui, Swift (Programming Language), Kotlin, Jetpack Compose, Adobe Suites
- **Published:** July 31, 2026
- **Apply:** https://adobe.wd5.myworkdayjobs.com/external_experienced/job/San-Jose/Software-Developer---Mobile_R169982

## About the Role

* 3-5 years shipping commercial mobile apps on Android or iOS. Proficient in Kotlin or Swift. Solid UI skills in Jetpack Compose, SwiftUI, or UIKit.
 * Experience with TypeScript or JavaScript in a hybrid web/native stack. Familiar with MVVM or Clean Architecture. Able to own tradeoffs, not just follow patterns.
 * Strong grasp of multi-threading, memory management, CI/CD, and automated testing. Enough foundation to know when AI output is right, when it's wrong, and when to go hands-on.

Nice to have

 * Experience on both iOS and Android. Familiarity with Lit, MobX, or Web Components. Background in creative or media apps. Published on the Play Store or App Store.

## Description

We're looking for a Software Developer to help Adobe Express Mobile ship with confidence. We're a mobile engineering team focused on making quality faster, smarter, and more scalable. We work independently and hold ourselves to a high bar. If that excites you, we'd love to meet you.
What you'll do

 * Work across Kotlin, Swift, and TypeScript to ship native capabilities that require real cross-layer understanding. Move fast without sacrificing correctness or craft.
 * Build AI-powered internal tools that help engineers develop, debug, and iterate faster. Apply deep platform knowledge to make sound architectural decisions.
 * Integrate with cloud-based device farms and CI/CD pipelines to support scalable testing and deployment. Bring development depth to decisions about tooling, coverage, and where AI fits.
 * Analyze automation results across device farms, OS versions, and CI runs. Turn signals into feedback loops that inform development and feed into agentic workflows that act on patterns as they emerge.


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