Software Engineer III - Android Developer- Business Banking

JPMorganChase•Plano, TX

About The Position

As a Business Banking Android Developer, you will deliver secure, scalable, and intuitive mobile experiences that help businesses manage their finances and grow with confidence. You will design, build, and maintain Android features, lead implementation of moderately complex initiatives, contribute to technical design decisions, and integrate the app with backend services. The role also involves developing and maintaining automated tests, improving app stability and performance, producing architecture and design artifacts, and using data insights to drive continuous improvement of software applications and systems. The position uses enterprise-authorized AI-assisted development tools and automation capabilities across the software development lifecycle. You will validate AI-generated outputs through peer review, automated testing, and secure coding practices, and contribute reusable patterns and learnings to improve team effectiveness. Responsible use of AI includes consideration of data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations.

Requirements

Formal training or certification in software engineering concepts.
At least 3 years of applied experience.
Practical experience with AI-assisted development tools, such as GitHub Copilot or code-generation tools, and understanding of how to integrate AI capabilities into development workflows.
Hands-on experience using enterprise-authorized AI-assisted software development tools for coding, test creation, troubleshooting, or documentation, with the ability to critically evaluate, validate, and refine outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations.
Strong hands-on Android development experience with Kotlin, Android SDK, and modern architecture patterns such as MVI, MVVM, or Clean Architecture.
Experience building user interfaces with Jetpack Compose and/or XML, including accessibility and responsive layout practices.
Experience with mobile testing practices and frameworks, including unit and instrumentation/UI tests, and troubleshooting complex issues.
Experience implementing or improving mobile CI/CD, including automated builds, quality gates, and release processes.

Nice To Haves

Experience with modularization, shared libraries, and scaling Android codebases across teams.
Experience with performance profiling and stability tooling, including startup-time, memory, crash analytics, and ANR monitoring.
Familiarity with mobile security best practices, including OWASP MASVS awareness, secure networking, secrets handling, and certificate pinning where applicable.
Experience with release strategies such as feature flags and phased rollouts, and operational readiness practices such as runbooks and monitoring.
Experience mentoring engineers and improving delivery metrics such as cycle time, defect escape, and app stability.

Responsibilities

Use enterprise-authorized AI coding-assistance tools to improve code quality, delivery speed, and productivity, validating outputs through peer review, automated testing, and secure coding standards.
Apply software development lifecycle tools, including authorized AI-assisted development and automation capabilities, to improve the value realized from automation.
Design, build, and maintain Android features using Kotlin and Java across devices and operating-system versions.
Lead implementation of moderately complex initiatives, including user interface flows, data and state management, and offline and error handling; contribute to technical design decisions.
Integrate with REST and GraphQL backend services, implement secure authentication flows, and ensure safe handling of local storage and network communications.
Build and maintain unit, instrumentation, and UI tests; improve app stability through crash reduction and ANR and performance tuning.
Produce architecture and design artifacts for complex applications and ensure software code development meets design constraints.
Gather, analyze, synthesize, and visualize data from large, diverse data sets to support continuous improvement of software applications and systems.
Identify hidden problems and patterns in data and use insights to improve coding hygiene and system architecture.
Contribute learnings and reusable AI-assisted development patterns to improve broader team effectiveness.
Guide peers on safe and effective use of AI-assisted development tools within team practices.