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Salary: USD 118,500 - 216,500 / annual
Life360 is a category-leading mobile app serving 102.4 million monthly active users across 180+ countries, offering location sharing, safe driver reports, crash detection with emergency dispatch, and pet GPS tracking. The company is building an AI-native organization where AI is integral to how teams build and operate.
The Revenue Experiences team (part of the Direct Revenue org) owns the premium experience behind Life360 membership, including subscription tiering, pricing, packaging, and all premium features members pay for. The team focuses on ownership and quality: extending the premium feature set with new capabilities while keeping existing services healthy, fast, and worth the price. Decisions are grounded in experimentation across paywalls, pricing, and ad placement.
You will be a Senior Software Engineer II joining a product-minded, AI-native engineering team where AI is treated as a first-class collaborator at every stage: ideation, coding, testing, review, and iteration. You'll own the end-to-end delivery of premium features and monetization surfaces, taking ideas from brief to shipped product serving 100M+ users. Success in your first year means owning several features or experiments that contribute to global revenue growth or improve quality of existing premium features.
Key responsibilities include:
- Design, build, and maintain premium features and services, owning quality from design through production
- Build subscription tiering, pricing, packaging surfaces: paywalls, plan selection, upsell/upgrade flows, and in-app purchase (IAP) flows
- Own quality of ads experience including placement, mediation, and performance/stability impact
- Partner with product, design, data science, and analytics to turn hypotheses into shippable work
- Work with AI (Claude Code or equivalent) as a primary collaborator, orchestrating agents for specs, code generation, testing, verification, and reviews
- Ship polished, performant, reliable experiences with strong attention to startup time, memory, battery, ANR, and crash-free rates
- Contribute to architectural decisions, code reviews, and culture of craft across mobile codebases
- Participate in on-call rotation and incident response
- Mentor other engineers and contribute to team processes and AI-native engineering practices
AI-native expectations: You use AI coding assistants daily for substantive tasks (analysis, coding, refactoring, testing, codebase navigation, documentation). AI-generated code receives the same review as any PR, and you are accountable for everything shipped. Senior engineers using AI well are expected to operate with meaningful leverage. You share what works, automate prompting strategies, help teammates adopt AI workflows, and stay current with evolving tooling.
REQUIREMENTS:
- 6+ years of Android software engineering experience shipping production apps at consumer scale
- Cross-platform experience including 1+ year of AI-assisted iOS development
- Experience with in-app billing and subscription platforms (Google Play Billing and StoreKit)
- Strong proficiency with Kotlin and Jetpack Compose (and Android View system); deep familiarity with modern Android toolchain (Android Studio, Kotlin Coroutines, Flow)
- Experience with Android architecture patterns (MVVM, MVI, Clean Architecture, Jetpack/ViewModel/Navigation, Hilt or Dagger) in large, multi-team codebases
- Comfort with mobile experimentation concepts: feature flagging, A/B testing, exposure logging, holdouts, guardrail metrics
- Solid grounding in mobile performance, memory, battery, ANR, and crash diagnostics (Android Studio Profiler, Perfetto/Systrace, Macrobenchmark, Crashlytics or equivalent)
- Experience with CI/CD for Android (Gradle, Fastlane, GitHub Actions, Bitrise, or similar) and modular build systems
- Strong technical expertise in LLM-powered agentic systems, prompt engineering, context-window optimization, and MCP-based integrations
- Clear communication of tradeoffs
- Bachelor's degree in a technical field or equivalent experience
OPTIONAL:
- Experience with mobile ad SDKs and mediation (AdMob, AppLovin MAX, or similar)
- Experience with experimentation platforms (Statsig, LaunchDarkly, Optimizely, Eppo, GrowthBook, or similar)
- Background in mobile analytics pipelines (Amplitude, Segment, Snowflake/Databricks downstream)
- Contributions to mobile open source or internal developer tooling
