Lead Software Engineer - ReactJS, UX

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 JPMorgan Chase within the Commercial & Investment Bank’s Sales & Research Technology team, you serve as a seasoned member of an agile team to design and deliver trusted, market-leading, user-facing technology products in a secure, stable, and scalable way. You are responsible for crafting intuitive, accessible, and high-performing user experiences while driving critical front-end technology solutions across various business functions in support of the firm’s business objectives.

Job responsibilities

• Executes software solutions with a strong emphasis on user interface design, development, and technical troubleshooting, with the ability to think beyond routine or conventional approaches to build engaging, responsive, and accessible experiences
• Creates secure and high-quality production code across the front-end stack and maintains reusable component libraries and design systems that scale across products
• Translates UX designs, wireframes, and prototypes into pixel-perfect, performant interfaces, partnering closely with product designers and UX researchers to deliver seamless user journeys
• Champions front-end best practices including responsive design, cross-browser compatibility, accessibility (WCAG), performance optimization, and modern state management patterns
• Integrates front-end applications with backend services and APIs (Java/Python) and cloud-hosted (AWS) platforms to deliver end-to-end functionality
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., component generation/refactoring, unit and UI test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness
• 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.
• Produces architecture and design artifacts for complex front-end applications while being accountable for ensuring design constraints, usability standards, and performance budgets are met
• Gathers, analyzes, and develops visualizations and dashboards from large, diverse data sets in service of continuous improvement of user-facing applications and systems
• Proactively identifies hidden usability issues and patterns in user behavior and telemetry data and uses these insights to drive improvements to UX quality and system architecture

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience building responsive, accessible user interfaces with modern front-end frameworks (e.g., React, Angular, or Vue) and core web technologies (HTML5, CSS3/Sass, TypeScript, JavaScript). Proficient in front-end development, including component-based architecture, state management, and consuming RESTful and/or GraphQL APIs
• Working knowledge of at least one backend language (Java or Python) and cloud services (AWS) sufficient to integrate, debug, and support end-to-end delivery
• Experience translating UX/UI designs and design systems (e.g., Figma) into production-ready code, with a strong eye for detail, usability, and accessibility
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, cod…