Software Engineer III - UI (React & Typescript)
JPMorgan Chase & Co. Hyderabad, Telangana, India
Financial Services · 10,001+ employees
About the role
You will design, develop, and troubleshoot secure software solutions within an agile team to enhance fraud protection products. The role involves leveraging AI-assisted tools to improve code quality and delivering architecture artifacts for complex applications.
What they look for
Requirements
Candidates must have at least 3 years of applied software engineering experience with proficiency in React, TypeScript, and Micro Frontend architecture. A solid understanding of agile methodologies, CI/CD, and secure coding practices is required.
Full description
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 the Payments Trust and Safety Technology group, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. You will be part of the Fraud Protection group, building solutions for merchants to protect themselves against fraudulent behavior. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- 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 3+ years applied experience
- Hands-on practical experience React, TypeScript / JavaScript, Redux / Redux Toolkit, GraphQL, HTML5 / CSS3, REST API integration
- Experience in React Router / frontend routing, Module Federation / Micro Frontends,
- Experience with Jest / React Testing Library or equivalent UI testing frameworks & Cypress / Playwright or equivalent UI automation framework
- 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.
- Experience working with Micro Frontend (MFE) architecture and independently deployable frontend applications.
- Experience with MFE integration, inter-MFE communication, routing, shared dependencies, and versioning.
- Hands on experience in integrating third-party/external MFEs with host applications.
- Experience troubleshooting MFE runtime, dependency, configuration, and communication issues.
- 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.
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies
- Exposure to cloud technologies
- Familiarity with cloud/containerized deployment and technologies such as Docker/Kubernetes is preferred.
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