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

• Premium Feature Development: Design, build, maintain, and enhance premium mobile features and services, taking ownership of quality and performance from initial design through production and ongoing improvement.
• Subscription and Revenue Experiences: Develop and optimize subscription tiering, pricing, packaging, and positioning experiences, including paywalls, plan selection interfaces, upgrade and upsell flows, and in-app purchase journeys.
• Cross-Platform Mobile Engineering: Contribute to Android development and AI-assisted iOS implementation, delivering consistent, intuitive, and reliable experiences across mobile platforms.
• AI-Native Development: Integrate AI coding assistants and agentic workflows into daily engineering activities, including specification development, code generation, testing, refactoring, code review, documentation, and iteration.
• AI Output Quality and Accountability: Evaluate AI-generated code critically, verify functionality, identify potential risks, and maintain full ownership of the reliability, security, and quality of shipped solutions.
• Performance and Reliability: Optimize mobile application startup time, memory consumption, battery usage, application-not-responding (ANR) rates, and crash-free performance to maintain a high-quality experience for a large global audience.
• Experimentation and Optimization: Collaborate with product, design, data science, and analytics teams to translate hypotheses into experiments and actionable product improvements. Use evidence to guide decisions on pricing, paywalls, advertising placement, and monetization strategies.
• Advertising Experience Quality: Maintain and improve advertising experiences, including ad placement and mediation, while minimizing negative impacts on application performance and stability.
• Technical Architecture and Code Quality: Contribute to architectural decisions, code reviews, engineering standards, and continuous improvement initiatives across mobile codebases.
• Production Support and Incident Response: Participate in on-call rotations, investigate production incidents, and resolve issues affecting premium features and releases.
• Technical Leadership and Mentoring: Support other engineers through mentoring, knowledge sharing, and collaborative problem-solving while helping establish effective AI-native engineering practices.
• Continuous Improvement: Identify opportunities to improve development workflows, automate repetitive tasks, share effective AI prompting strategies, and introduce tools that enhance team productivity and delivery speed.
• End-to-End Ownership: Deliver multiple features or experiments that contribute to revenue growth or improve the quality and reliability of existing premium experiences during the first year.

Requirements:

• Professional Experience: At least 6 years of Android software engineering experience, with a proven track record of shipping production mobile applications at consumer scale.
• Cross-Platform Development: Experience working across mobile platforms, including at least 1 year of AI-assisted iOS development.
• Subscription and Payment Systems: Hands-on experience with mobile in-app billing and subscription platforms, including Google Play Billing and Apple StoreKit.
• Android Development Expertise: Strong proficiency in Kotlin, Jetpack Compose, and the Android View system, with deep familiarity with Android Studio, Kotlin Coroutines, and Flow.
• Mobile Architecture: Experience applying Android architecture patterns and technologies such as MVVM, MVI, Clean Architecture, Jetpack, ViewModel, Navigation, Hilt, or Dagger within large, multi-team codebases.
• Mobile Performance Engineering: Strong understanding of mobile performance optimization, memory management, battery consumption, ANR diagnostics, and crash analysis. Familiarity with tools such as Android Studio Profiler, Perfetto, Systrace, Macrobenchmark, and Crashlytics or equivalent platforms is expected.
• Experimentation and Analytics: Understanding of feature flags, A/B testing, exposure logging, holdout groups, and guardrail metrics, with the ability to use experimentation insights to guide product decisions.
• Build and Release Infrastructure: Experience with Android CI/CD workflows, Gradle, modular build systems, and tools such as Fastlane, GitHub Actions, or Bitrise.
• AI and Agentic Systems: Strong technical expertise in LLM-powered agentic systems, prompt engineering, context-window optimization, and integrations based on the Model Context Protocol (MCP).
• AI-Assisted Engineering Practices: Demonstrated ability to use AI coding assistants, such as Claude Code, Cursor, or GitHub Copilot, for meaningful engineering tasks, including code analysis, implementation, refactoring, testing, and documentation.
• Engineering Judgment: Ability to evaluate AI-generated solutions critically, validate correctness, identify limitations, and remain accountable for code quality and production outcomes.
• Technical Communication: Strong communication skills and the ability to explain technical trade-offs, architectural decisions, and implementation approaches clearly to technical and non-technical stakeholders.
• Ownership and Initiative: A proactive, product-minded approach to engineering, with the ability to independently manage complex tasks, prioritize effectively, and deliver measurable outcomes.
• Education: Bachelor's degree in a technical discipline or equivalent practical experience.

Nice-to-Have Qualifications:

• Experience with mobile advertising SDKs and mediation platforms, including AdMob, AppLovin MAX, or similar solutions.
• Familiarity with experimentation platforms such as Statsig, LaunchDarkly, Optimizely, Eppo, or GrowthBook.
• Experience with mobile analytics pipelines and data platforms, including Amplitude, Segment, Snowflake, or Databricks.
• Contributions to mobile open-source projects or internal developer tooling.
• A demonstrated interest in emerging AI development tools and a willingness to share best practices that improve team-wide engineering productivity.

Benefits:

• Competitive Canadian compensation: Annual salary range of CAD $171,500–$201,000, with final compensation determined by relevant experience, job-related skills, knowledge, and geographic location.
• Equity compensation: Restricted Stock Units (RSUs) as part of the overall compensation package.
• Comprehensive healthcare coverage: Medical and dental benefits, with supplemental plans available to Canadian employees.
• Life and disability insurance: Coverage options to support financial security and employee well-being.
• Retirement savings: Registered Retirement Savings Plan (RRSP) with a Deferred Profit Sharing Plan (DPSP) for Canadian employees.
• Flexible paid time off: Generous flexible PTO, companywide holidays, and dedicated summer and winter shutdown periods.
• Paid parental leave: Support for employees welcoming a new child.
• Mental health and wellness: Access to mental wellness resources and an Employee Assistance Program (EAP).
• Remote-first work environment: The flexibility to work remotely within Canada, supported by equipment, tools, and reimbursement resources for an effective home office.
• Learning and development: Opportunities to expand technical expertise, strengthen AI engineering capabilities, and participate in professional development programs.
• Premium membership perks: Complimentary premium membership and tracking devices as part of the employee benefits package.
• AI-native engineering culture: The opportunity to work with modern AI tools, influence emerging engineering practices, and help shape how AI is integrated into software development.
• Inclusive workplace: A commitment to equal opportunity, diversity, and creating an environment where employees can contribute authentically and grow professionally.