Shape the future of enterprise technology — join a team where your full stack expertise drives real impact across one of the world's most complex financial institutions.
As a Software Engineer III at JPMorganChase within Corporate Technology, you will apply proficient full stack engineering skills to design, build, and evolve modern, resilient applications that support controls and operational risk outcomes across critical corporate functions — including Finance, Risk Management, Human Resources, Compliance, and Legal. You will contribute to architecture and design discussions, translate requirements into robust technical solutions, and ensure implementations meet the performance, security, and scalability demands of a large, regulated financial institution. Your work will directly strengthen the firm's technology controls agenda and support the delivery of scalable corporate systems that matter.
Job responsibilities
- Design and deliver full stack applications using Java (8+), Spring Boot microservices, and Angular (6+), ensuring solutions are resilient, secure, and aligned to enterprise architecture standards
- Build and evolve well-designed REST APIs, applying strong microservices patterns, core design principles, and pragmatic tradeoffs appropriate for regulated enterprise environments
- Write clean, testable, and maintainable code with a disciplined approach to quality, including automated testing and active participation in peer code reviews and collaborative design sessions
- Support and improve CI/CD pipelines, branching strategies, and release discipline to enable frequent, safe deployments in a controlled environment
- Troubleshoot and resolve production issues through structured root-cause analysis, implementing preventative fixes that improve system stability and reduce operational risk
- Collaborate with product owners, UX designers, and cross-functional engineering partners to shape solutions that are usable, accessible, and scalable
- Contribute to shared standards, reusable templates, and common components that improve consistency and accelerate delivery across the team
- 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 experience building full stack applications using Java (8+) and Angular (6+), with practical experience delivering Spring / Spring Boot microservices and well-designed REST APIs
- Proficiency in TypeScript, HTML, CSS, and JavaScript with strong attention to UX detail and quality
- Demonstrated ability to write clean, testable code supported by automated testing practices, with active participation in code reviews and collaborative design sessions
- Understanding of microservices patterns, core design principles, and common design patterns, with a pragmatic approach to tradeoffs in enterprise environments
- Working proficiency with modern Software Development Life Cycle toolsets and practices, including CI/CD, branching and versioning strategy, and release discipline suitable for regulated environments
- Awareness of secure coding practices, API security considerations, access control concepts, and resilience expectations in enterprise environments
- Clear communication and collaboration skills, with demonstrated ability to work effectively with distributed teams and diverse stakeholders
- 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 observability and production support practices, including monitoring, logging, alerting, performance tuning, and structured incident and problem management in enterprise systems
- Exposure to cloud-native patterns, containerization, and platform modernization approaches
- Experience partnering closely with UX teams to prototype and iterate on user flows and interaction patterns
- Agile delivery experience, including iterative development, estimation, and continuous improvement practices