AI-First Android Engineer
$175,000–$225,000 year
Remote · California, United States or New York, United States
Job Summary
AI-First Android Engineer leading an AI-driven Android surface with end-to-end ownership from discovery to production. Manage multiple AI coding agents to design, build, test, and ship Android features in Kotlin, while shaping architecture (Clean Architecture, MVVM, multi-module Gradle, DI with Koin, Coroutines/Flow, Moshi) and directing an engineer-as-a-team workflow (spec drafting, codegen, test generation, code review, refactoring, doc writing, bug triage). Design prompts, evals, and guardrails for repeatable AI-driven mobile development; set up automation for CI/CD and distribution; monitor production health with Sentry/Datadog/ Firebase, triage incidents, and re-prioritize backlogs. Collaborate on architecture decisions, drive AI-native development practices, and mentor a contractor team. Requirements include extensive Android experience, proficiency with modern AI tooling, REST/JSON:API integration, and a strong ownership mindset. Compensation ranges from $175,000 to $225,000, with eligibility for annual incentive and equity. Remote eligibility is limited to specified US states.
Required Qualifications
- 5–8 years of professional Android development experience with a portfolio of shipped consumer apps at scale
- Native, demonstrable fluency with modern AI coding tooling (Claude Code, Cursor, Copilot, Codex, agentic workflows)
- Strong, opinionated taste in Kotlin and modern Android architecture (Clean Architecture, MVVM, multi-module Gradle, DI, Coroutines/Flow, Moshi)
- Comfort working in a DataBinding/XML codebase today, with the judgment to drive a phased Compose migration when and where it’s worth it
- Experience integrating with REST + JSON:API-style backends and the Shopify Buy/Checkout SDKs at consumer scale
- A bias toward owning end-to-end outcomes rather than handing off work at team boundaries
- Genuinely autonomous in operation: you read dashboards on your own and prioritize your own queue
- Comfort writing prompts, evals, and guardrails — treat AI as a system to be engineered
- Sharp written communication and collaboration in a distributed team
- Collaborative, ego-light disposition — open to design critique
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