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
