JPMorgan Chase
From JPMorgan Chase's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorganChase within Risk Technology, you are a seasoned member of an agile team focused on designing and delivering trusted, market-leading technology products in a secure, stable, and scalable way. You bring technical depth across the full stack — from modern React and TypeScript frontends to Java and Spring Boot backend services — and you thrive in an environment where your contributions directly support the firm's risk management objectives. This is your opportunity to grow alongside talented engineers, influence technical direction, and make a meaningful impact at one of the world's leading financial institutions.
Job responsibilities
Execute software solutions across design, development, and technical troubleshooting, thinking beyond conventional approaches to break down complex problems and build scalable solutions
Create secure, high-quality production code and maintain algorithms that run synchronously with appropriate systems
Produce architecture and design artifacts for complex applications, ensuring design constraints are met throughout the software development lifecycle
Build and maintain full-stack features in close partnership with product and design teams to deliver high-quality, accessible user experiences
Develop modern web interfaces using React and TypeScript, leveraging reusable components and patterns aligned to established design systems
Ensure user interface implementations follow accessibility best practices, including keyboard navigation, semantic markup, and assistive technology support
Design and implement backend services and APIs using Java and Spring Boot, including integration with data stores and downstream systems
Gather, analyze, and synthesize large, diverse data sets to develop visualizations and reporting that drive continuous improvement of software applications
Proactively identify hidden problems and patterns in data, using insights to improve coding hygiene and system architecture
Contribute to software engineering communities of practice and events that explore new and emerging technologies
Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards
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 proficient applied experience
Hands-on practical experience in system design, Frontend application development, testing, and operational stability
Proficient in coding in one or more languages, with demonstrated strength in Java and building services with Spring Boot or equivalent frameworks
Strong experience building frontend applications with React and TypeScript
Experience working with design systems and component libraries, applying consistent user interface standards at scale
Working knowledge of web accessibility principles and implementing accessible user interface patterns
Experience developing, debugging, and maintaining code in a large-scale environment using one or more modern programming languages and database querying languages
Solid understanding of agile methodologies, including continuous integration and delivery, application resiliency, and security practices
Demonstrated knowledge of software applications and technical processes within a technical discipline such as cloud, artificial intelligence, machine learning, or mobile
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations
Familiarity with modern frontend technologies, including state management patterns, build tooling, and testing frameworks
Experience with API design and integration patterns, including REST; exposure to event-driven architectures is a plus
Exposure to cloud technologies and cloud-native development practices
Experience building automated tests across the stack, including unit, integration, and user interface testing
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