Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer at JPMorganChase's Consumer and Community Banking's Connected Banking and Personal Financial Management team , you’ll lead engineering innovation through the architecture, development, and evolution of scalable, resilient products. You’ll use your technical depth to challenge traditional approaches, drive sound engineering practices, and foster a culture of continuous improvement. Partnering closely with Product, Design, Data, and Operations, you’ll align teams around a clear technical strategy and deliver solutions that address customer needs with speed, quality, and reliability.
Job responsibilities
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Serves as a function-wide subject matter expert in one or more areas of focus
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Proficiency in technologies like Java, Spring Boot, Containerization(Docker and Kubernetes), Cassandra or any NO SQL DB.
- Proficiency in any of the front end technology like React/ReactJS, Redux, Angular/AngularJS, ExtJS, JQuery, NodeJS
- Hands on experience in Microservices, RESTful microservices development.
- Experience with messaging and integration frameworks like Kafka
- Experience developing with testing frameworks such as JUnit, Mockito, Karma, Protractor, Jasmine, Mocha, Selenium, and Cucumber.
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
- Ability to tackle design and functionality problems independently with little to no oversight
Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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
- Experience working in a financial services environment.
- Technology coach, and leader to help team solve technology problems.