Lead Software Engineer - Java/Fintech
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As an Equity Derivative Group software engineer at JPMorgan Chase within our agile team, you will join us in creating, transforming, and supporting our global equity derivatives sales & marketing platforms using modern technologies and industry best practices.
Job responsibilities
- Collaborates with engineers, business analysts, project managers, and sales and marketers to develop software solutions for our Equity Derivatives platform
- Works within a team of software engineers analyzing and implementing business requirements within an Agile/Scrum environment
- Works closely with production management applying technical knowledge to support business processes, changes, and end users
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- 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
- Experience with Java/JVM and the Java/JVM ecosystem
- Well-rounded software engineering skills across end-to-end software lifecycle
- Good understanding of software design patterns and clean code practices
- Strong written and oral communication skills
- Experience working on financial systems
- Experience partnering with product and engineering teams
- Able to work on a diverse team
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Preferred qualifications, capabilities, and skills
- Experience with object-oriented design and micro-service architectures and best practices
- Experience with finance / derivative products
- Experience with the Java ecosystem including Spring, Web Services, and Messaging
- Experience with NoSQL / Big Data Databases and Cloud technologies
- Experience with Java 11+ and / or additional JVM languages like Kotlin/Scala
- Exceptional client relationship skills including the ability to discover true requirements underlying feature requests, recommend alternative technical approaches, and or drive efforts to meet committed timelines with optimal solutions