Senior Software Engineer II, Mobile - Revenue Experimentation (AI Native)
$118.5k - $216.5kjobgether
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 incomplete hypothesis or loosely defined problem and independently move it toward a working product experience.
- Demonstrated ability to own technical outcomes throughout design, development, deployment, experimentation, and production support.
- Strong product judgment and engineering craft, with the ability to articulate what makes an effective experiment, rollout, and user experience.
- Excellent communication and collaboration skills, including the ability to work effectively with cross-functional teams and give and receive constructive feedback.
- Bachelor's degree in a technical field or equivalent practical experience.
- Experience with experimentation platforms such as Statsig, LaunchDarkly, Optimizely, Eppo, or GrowthBook is a plus.
- Familiarity with mobile analytics platforms and pipelines such as Amplitude, Segment, Snowflake, or Databricks is desirable.
- Knowledge of Bayesian or sequential testing methodologies and their implications for client-side experimentation is an advantage.
- Experience with subscription, paywall, pricing, onboarding, or other monetization surfaces at consumer scale is valuable.
- Deep expertise in at least one of Kotlin/Android, Swift, or React, with the ability to work comfortably across another platform.
- Contributions to mobile open source projects or internal developer tooling are a plus.
Benefits:
- U.S. salary range of $118,500–$216,500 USD, with final compensation influenced by location, background, job-related knowledge, skills, and experience.
- Canadian salary range of $171,500–$201,000 CAD for eligible Canadian employees.
- Total compensation includes equity in the form of Restricted Stock Units (RSUs).
- Comprehensive medical, dental, vision, financial, and other benefits.
- Medical, dental, vision, life, and disability insurance, with U.S. employee medical, dental, and vision coverage fully paid.
- 401(k) with company matching in the U.S. and RRSP with DPSP for Canadian employees.
- Paid parental leave.
- Mental Wellness Program and Employee Assistance Program.
- Flexible paid time off, company holidays, and summer and winter shutdown periods.
- Learning and development programs.
- Equipment, tools, and reimbursement support for remote work.
- Free premium membership and tracking-device benefits.
- Remote-first work environment for eligible employees in the U.S. and Canada.
- Opportunity to work on high-scale mobile experimentation affecting a large global user base.
- Opportunity to shape AI-native engineering workflows and influence practices across the broader mobile organization.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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