Not specified
Senior Software Engineer II, Mobile - On App Ads (AI Native)
- Location
- Canada
- Work type
- Remote · Full-time
- Salary
- Not listed
- Posted
- (3 days ago)
About the role
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 – On App Ads (AI Native) based in Canada.
Join a remote-first technology team developing innovative mobile experiences that help families stay connected, safe, and informed. As a Senior Mobile Software Engineer, you will play a key role in building and scaling the in-app advertising infrastructure across iOS applications. You will own critical components of the advertising ecosystem, including SDK development, demand partner integrations, ad mediation, privacy frameworks, and new advertising formats. Working primarily with Swift, you will help optimize advertising performance, improve monetization, and ensure a seamless user experience across a large-scale mobile platform. You will also embrace AI-native engineering practices, using intelligent coding agents to accelerate development, improve testing, and enhance technical workflows. This is an opportunity to combine advanced mobile engineering, advertising technology, and AI-driven innovation while collaborating with distributed teams and external technology partners.
Accountabilities:
Requirements:
At least six years of professional iOS software engineering experience, with a proven track record of delivering and maintaining production applications at significant scale. Strong proficiency in Swift, SwiftUI, and UIKit, alongside practical experience with modern iOS development tools and frameworks, including Xcode, Swift Concurrency, and Combine. At least one year of hands-on experience working with Large Language Models (LLMs), including prompting, evaluating, and integrating AI-assisted development tools into engineering workflows. Strong understanding of iOS architecture patterns, including MVVM, coordinators, dependency injection, and modularization using Swift Package Manager (SPM) or CocoaPods. Experience integrating, maintaining, and troubleshooting third-party SDKs in production environments, including managing version upgrades, closed-source dependencies, application size, and performance considerations. Solid understanding of iOS performance optimization, memory management, and crash diagnostics, with experience using tools such as Instruments, MetricKit, and Crashlytics or equivalent platforms. Experience with iOS continuous integration and deployment (CI/CD) tools, such as Fastlane, Xcode Cloud, Buildkite, or GitHub Actions. Practical experience with AI-native and agentic development workflows, including prompt engineering, context-window management, MCP, and function calling. Demonstrated ability to use AI coding assistants for substantive engineering activities, including analysis, implementation, refactoring, testing, documentation, and codebase navigation. Strong technical judgment and accountability, with the ability to critically review AI-generated code and ensure the reliability, security, and maintainability of delivered solutions. Bachelor's degree in computer science, software engineering, or another technical discipline, or equivalent professional experience. Strong problem-solving abilities, with a growth-oriented mindset and willingness to explore technologies and responsibilities beyond your immediate specialization. Excellent communication and collaboration skills, with the ability to explain technical decisions, discuss trade-offs, and work effectively with cross-functional teams and external partners. A strong sense of ownership, taking responsibility for projects throughout their entire lifecycle, from initial design and implementation to production monitoring and ongoing improvements.Nice-to-Have Qualifications:
Previous experience in advertising technology, particularly OpenRTB, Prebid Mobile, Google Mobile Ads, Google Ad Manager (GAM), AdMob, AppLovin MAX, or Unity LevelPlay. Knowledge of iOS privacy and attribution technologies, including ATT, SKAdNetwork, AdAttributionKit, Privacy Manifests, and consent management platforms such as Google UMP and TCF/GPP. Experience developing or maintaining software development kits (SDKs) or reusable frameworks consumed by multiple engineering teams. Familiarity with advertising quality tools, creative rendering technologies such as WKWebView and MRAID, and troubleshooting advertising fill rates, latency, and rendering performance. Experience with experimentation and feature management platforms such as Statsig, LaunchDarkly, or Optimizely. Knowledge of Android development and Kotlin, or a willingness to contribute to cross-platform engineering initiatives. Experience mentoring engineers, establishing technical standards, and introducing scalable development practices.AI-Native Engineering Expectations:
Daily AI adoption: Regularly use AI coding tools such as Claude Code, Cursor, and GitHub Copilot for meaningful development tasks, including coding, testing, refactoring, analysis, and documentation. Technical judgment and ownership: Critically assess AI-generated outputs, apply the same quality standards as traditional code contributions, and remain accountable for everything delivered. Engineering productivity: Use AI effectively to increase development speed, improve quality, and independently tackle complex technical challenges. Knowledge sharing: Develop reusable prompting strategies, document successful AI workflows, and support colleagues in adopting AI-assisted development practices. Continuous innovation: Stay informed about emerging AI tools and techniques, experiment with new approaches, and recommend improvements that create measurable value for the engineering team.