Full Stack Software Engineer II - Java, React
Headquartered in New York City, JPMorgan Chase is the largest bank in the United States.
You will work with Java, Spring Boot, Hibernate, JPA, Spring Kafka, microservices, CI/CD, and AI-assisted coding tools; preferred skills include React, Angular, Kubernetes, and Python. You’ll build production-grade full-stack software that powers JPMorgan’s global banking businesses and supports millions of customers.
Free Tailor for ATS: 10/10 runs left
Build real, production-grade software that powers our global banking businesses. At JPMorganChase, we believe great engineers are made through meaningful challenges, strong mentorship, and a culture that rewards curiosity and craftsmanship. Here, you'll work alongside experienced engineers who are passionate about clean code, scalable architecture, and continuous improvement — and you'll have the opportunity to explore emerging technologies like AI and GenAI from day one.
As a Software Engineer II at JPMorganChase within [Insert Team Name / Line of Business], you will ship secure, full-stack features, write clean Java code, and deepen your expertise in modern engineering practices — including microservices, event-driven architecture, and CI/CD — while building the foundation for a serious, long-term engineering career. You'll tackle real debugging and performance challenges, automate away recurring issues, and contribute to a team culture centered on fast feedback, strong code reviews, and scalable design. This role offers you the opportunity to grow quickly, make a visible impact, and help shape the technology that serves millions of customers worldwide.
Job responsibilities
Design and deliver creative software solutions, contributing to the full development lifecycle — from design and development through to technical troubleshooting and problem resolution
Build secure, high-quality production code and review and debug code written by others to improve overall quality and maintainability
Identify and implement automation and sustainable fixes for recurring issues to improve the operational stability and resiliency of applications and systems
Partner in technical evaluations with external vendors, startups, and internal teams by contributing to outcomes-oriented reviews of architecture, technical capabilities, and platform fit
Contribute to communities of practice across software engineering by sharing knowledge, supporting adoption of modern technologies, and promoting engineering best practices
Leverage 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
Apply 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
Support a team culture that values diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and expanding applied experience
Hands-on experience contributing to system design, application development, testing, and production support and operational stability
Strong proficiency in Java and common frameworks such as Spring Boot, Hibernate, JPA, and Spring Kafka
Working knowledge of microservices architectures and Kafka or other messaging and event-driven architectures
Experience with automation and continuous delivery practices, including build and test automation and CI/CD pipelines
Proficiency across the Software Development Life Cycle including requirements, design, implementation, testing, release, and support
Good understanding of Agile delivery, including CI/CD concepts, application resiliency, and secure engineering practices
Demonstrated ability to develop within at least one technical discipline such as cloud, data, 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
Experience with additional languages and frameworks such as .NET (C#) and Python
Familiarity with modern front-end technologies such as React and/or Angular
Experience with container platforms and platform-as-a-service environments, including Kubernetes and Cloud Foundry
Familiarity with Generative AI tools and patterns such as prompt engineering, retrieval-augmented generation, vector search and embeddings, and safe and secure adoption practices