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JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.
As a Software Engineer III at JPMorganChase within the Climate Nature & Social Risk Technology team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Own delivery of complex UI features using React and TypeScript, aligned to a design system and front-end engineering standards.
- Lead UI technical design (component architecture, state management, API integration patterns, routing, error handling) and document key decisions.
- Drive quality and operability through automated testing (unit/component/e2e), accessibility compliance, performance optimization, and UI telemetry/monitoring.
- Build and improve CI/CD for UI delivery (linting, automated tests, quality gates, build optimization, release automation) and reduce flaky tests.
- Use JPMorganChase-approved AI-assisted development tools (e.g., Claude AI where approved) to accelerate refactoring, feature changes, test generation, and documentation with rigorous human validation.
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit 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.
- 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 applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and applied experience
- Strong hands-on experience building enterprise web applications with React + TypeScript, including advanced component patterns.
- Strong experience with UI testing (e.g., Jest/React Testing Library and Cypress/Playwright) and systematic debugging/troubleshooting.
- Proven experience designing and delivering accessible, performant UIs (WCAG awareness, profiling, bundle optimization).
- Proven experience implementing and improving CI/CD for front-end applications with automated quality gates.
- Disciplined experience using AI coding assistants (Claude AI or equivalent where approved) with verification and secure usage practices.
- 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.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
- Experience with design systems at scale (component libraries, theming/tokens, governance) and cross-team adoption.
- Experience with modern UI architecture patterns (micro-frontends/module federation, SSR frameworks such as Next.js, BFF patterns).
- Experience with web observability (RUM, client logging, correlation with backend signals) and feature-flag driven delivery.
- Track record reducing defect escape and flaky tests, improving release confidence and developer productivity.
- Experience mentoring engineers and leading technical initiatives within a squad or across teams.
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