Senior Software Engineer II, Mobile - Revenue Experimentation (AI Native)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Software Engineer II, Mobile - Revenue Experimentation (AI Native) based in United States.

This is a senior mobile engineering role focused on building and scaling revenue and growth experimentation across a high-traffic consumer application. You will turn product hypotheses and data insights into production-ready experiments spanning subscriptions, pricing, advertising, purchases, and upgrade experiences. The role combines strong Android engineering with experimentation, analytics, performance, and AI-native development practices. You will work closely with Product, Design, Data Science, and Analytics teams to rapidly test ideas and turn results into informed product decisions. As an AI-native engineer, you will use agentic tools throughout ideation, coding, testing, review, and iteration. The role offers significant ownership, technical influence, and the opportunity to establish engineering practices adopted across the broader mobile organization.

Accountabilities:

• Design, build, and launch high-quality Android growth and monetization features, including subscription paywalls, pricing experiments, advertising placements and mediation, in-app purchases, and upsell or upgrade flows.
• Own multiple concurrent experiments from hypothesis through production, translating rough ideas, data insights, or partially defined briefs into safely instrumented experiences.
• Partner with Product, Design, Data Science, and Analytics to translate hypotheses into shippable experiments, evaluate results, and determine subsequent product decisions.
• Challenge assumptions and proposed approaches when data or technical evidence suggests that a hypothesis or plan should be reconsidered.
• Use AI coding assistants and agentic workflows as first-class development collaborators for specifications, implementation, testing, analysis, code review, and iteration.
• Instrument experiments accurately through exposure logging, analytics, holdouts, and appropriate guardrail metrics so downstream decisions are based on trustworthy results.
• Deliver performant and reliable Android experiences to a large consumer audience, with close attention to startup performance, memory, battery usage, ANR rates, and crash-free performance.
• Move quickly from ambiguous concepts to working experiences, using early releases as learning opportunities and iterating based on real-world results.
• Help establish and document AI-native Android engineering practices, workflows, and playbooks that can be adopted across the broader mobile organization.
• Contribute to architecture decisions, code reviews, technical standards, and continuous improvement of the Android codebase.
• Participate in on-call rotations and incident response related to mobile experiments and releases.
• Mentor other engineers and contribute to team processes, technical standards, and the continued evolution of AI-native engineering practices.

Requirements:

• 6+ years of professional Android software engineering experience building and shipping production applications at consumer scale.
• At least 1 year of hands-on experience prompting, evaluating, and building with large language models.
• Strong Kotlin and Jetpack Compose expertise, along with deep familiarity with the modern Android development ecosystem, including Android Studio, Kotlin Coroutines, and Flow.
• Experience with Android architecture patterns and frameworks such as MVVM, MVI, Clean Architecture, Jetpack ViewModel, Navigation, Hilt, or Dagger within large, multi-team codebases.
• Practical experience with mobile experimentation concepts including feature flags, A/B testing, exposure logging, holdouts, and guardrail metrics.
• Strong understanding of mobile performance, memory, battery, ANR, and crash diagnostics, using tools such as Android Studio Profiler, Perfetto/Systrace, Macrobenchmark, Crashlytics, or equivalent technologies.
• Experience with Android CI/CD and build systems, including Gradle, Fastlane, GitHub Actions, Bitrise, or similar platforms, as well as modular application architectures.
• Deep experience with agentic development workflows, prompt engineering, context-window management, and MCP/function calling, with the judgment to use AI as leverage without outsourcing engineering decisions to agents.
• Strong ownership and agency, with the ability to take an …