Full-Stack Software Engineer III
Headquartered in New York City, JPMorgan Chase is the largest bank in the United States.
Design, develop, and deliver full-stack solutions using React, Node.js/TypeScript, and Python. As part of JPMorganChase’s Infrastructure Platforms Data Center Services team, you will build and enhance technology products that power global market infrastructure. The role includes mentoring junior engineers.
Free Tailor for ATS: 10/10 runs left
Join a team that is redefining how enterprise infrastructure technology is built, delivered, and scaled. At JPMorganChase, we invest in our engineers — giving you access to cutting-edge tools, meaningful mentorship, and the opportunity to grow your career across one of the world's most complex and innovative technology organizations. Here, your work doesn't just support a product — it powers the infrastructure that keeps global markets moving.
As a Software Engineer III at JPMorganChase within the Infrastructure Platforms, Data Center Services team, you serve as a seasoned member of an agile team that works to enhance, build, 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. In this role, you will bring both technical depth and collaborative energy to a team that values quality, innovation, and continuous improvement.
Job Responsibilities
Apply advanced technical skills to design, develop, and deliver full-stack solutions across frontend (React) and backend (Node.js/TypeScript, Python) services
Create secure, high-quality production code and maintain algorithms that run reliably and synchronously with appropriate systems
Produce architecture and design artifacts for complex application components, ensuring design constraints are met in implementation
Gather, analyze, synthesize, and develop visualizations from large data sets in support of continuous improvement of software applications
Proactively identify hidden problems and patterns in data, and use these insights to drive improvements to coding hygiene and system architecture
Develop subject matter expertise in a specific technical domain relevant to Data Center Services (e.g., UI/UX, backend architecture, software development lifecycle tooling, testing strategy, or operational support)
Contribute to software engineering communities of practice and employee resource groups through facilitation, guest speaking, or content contribution
Mentor junior software engineers and actively support their technical growth and development
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, application development, testing, and operational stability
Proficiency in modern programming languages, with strong experience in JavaScript/TypeScript (React, Node.js) required
Experience developing, debugging, and maintaining code in a large-scale environment using modern programming and database querying languages
Solid understanding of agile methodologies, including continuous integration/continuous delivery, application resiliency, and security practices
Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence/machine learning, or mobile)
Working knowledge of the Software Development Life Cycle
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 Python for backend services or tooling
Exposure to cloud technologies and infrastructure-as-code practices
Experience with artificial intelligence or machine learning concepts and tooling relevant to infrastructure and operations use cases