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
Preferred qualifications, capabilities, and skills
- 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