Software Engineer III (Java)

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 Technology division, you serve as a seasoned member of an agile team to design 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.

Job responsibilities
- Executes standard software solution, design, development, and technical troubleshooting
- Writes secure and high-quality code using the syntax of at least one programming language with limited guidance
- 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.
- Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
- 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
- Applies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity
- Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
- Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience
- Demonstrated ability to code in Java, Spring
- Working knowledge of using enterprise-authorized AI capabilities within the work environment to support software engineering workflows with strong validation habits and awareness of data sensitivity.
- Ability to use AI coding assistants, prompting, skills, MCPs. Ability to review and validate AI-assisted code and technical recommendations before use, escalating when uncertain and following security and data handling requirements. Awareness of tokens/context windows and how LLMs work.
- Ability to work in large, collaborative teams to achieve organizational goals, with a passion to build an inclusive and innovative culture
- Understanding of software skills such as business analysis, development, maintenance, and software improvement
- Proficiency in developmental toolsets
- Object-oriented design & basic design principles - encapsulation, interfaces, SOLID awareness, simple patterns
- Version control (Git) - branching, pull requests, rebasing/merging, resolving conflicts.
Preferred qualifications, capabilities, and skills
- Exposure to cloud technologies Containers basics — Docker fundamentals, images vs containers.
- CI/CD basics — what pipelines do, how to debug
- Observability basics — logging, metrics

- HTTP & REST fundamentals – JSON, status codes, auth basics, pagination, idempotency
- Proficiency in database skills - SQL basics (joins, indexes at a high level), ORMs, data modeling fundamentals AWS DBs a plus (Aurora/RDS)

- Security basics — input validation, secrets handling, least privilege, common vulnerabilities. OWASP awareness is a plus