Lead Software Engineer - IOS

We have an opportunity to impact your career and provide an adventure where you can push the limits of what’s possible. 

As a Lead Software Engineer at JPMorganChase within the Asset and Wealth Management, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. 

Job responsibilities

• Lead mobile delivery across multiple concurrent projects, from concept through production, across the full SDLC.
• Own iOS/iPadOS technical direction, including:
  • Architecture (e.g., MVVM, Clean Architecture, modular Swift packages). Coding standards and best practices. Performance, reliability, and user experience
• Translate business requirements into technical designs in partnership with analysts, architects, and UX designers.
• Write and review secure, high-quality code; integrate with back-end services and microservices via REST/JSON. Build reusable UI components and modernize legacy code (e.g., Objective-C/UIKit to Swift/SwiftUI).
• Contribute to Android features and code reviews to keep behavior consistent across platforms. Mentor iOS and Android engineers; promote Agile practices such as Scrum and TDD/BDD.
• Drive adoption of enterprise-authorized AI-assisted engineering practices (e.g., code review/refactoring, test acceleration, root-cause analysis) with consistent validation standards (secure coding, peer review, automated testing).
• Own production health: resolve crashes, performance and authentication issues, automate remediation, keep platforms current, and lead safe App Store/Play Store releases. Evaluate emerging technologies, vendors, and startups for fit with existing systems.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Bachelor’s degree in an engineering field.
• Advanced proficiency in Swift, Xcode, SwiftUI/UIKit, Combine, Swift Concurrency, Swift Package Manager, and Instruments; working knowledge of Objective-C.
• Working knowledge of Kotlin, Android SDK, Jetpack Compose, and Gradle. Proven track record building maintainable, high-quality mobile apps and leading mobile teams or workstreams.
• Experience leading the use of approved AI-assisted development tools, including validating AI outputs for correctness, performance, and security. Understanding of responsible AI use (data sensitivity, secure handling of inputs/outputs) and ability to coach engineers on safe, compliant adoption.
• Strong mobile security knowledge, including Keychain/Keystore, encryption in transit, certificate pinning, biometrics, and modern authentication. Experience with CI/CD (Git, Jenkins), automated regression testing (XCTest/XCUITest), observability, and App Store/Play Store publishing.
• Excellent analytical and communication skills; able to work across globally distributed teams. Knowledge of the financial services industry and practical cloud-native experience.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

**Preferred qualification…