Lead Software Engineer -Full Stack Java/Spring/AWS

JPMorganChase•Jersey City, NJ

About The Position

We have an opportunity to help you grow your career through challenging work where you can build reliable technology at scale. As a Lead Software Engineer at JPMorgan Chase within the Consumer & Community Banking team, you are an integral part of an agile team that enhances, builds, and delivers secure, stable, and scalable technology products. As a core technical contributor, you are responsible for delivering critical technology solutions across multiple technical areas and business functions in support of the firm’s objectives.

Requirements

Formal training or certification on software engineering concepts and 5+ years applied experience.
Hands-on experience in software engineering, including system design, application development, testing, and operational support.
Proficiency in back-end development (e.g., Java, Spring Boot) with experience building microservices-based applications.
Experience with cloud platforms (e.g., AWS, Azure, GCP) and building services for scalability, reliability, and performance.
Experience with distributed systems and web technologies, including RESTful APIs, web services, WebSockets, and JSON.
Experience working with agile development methodologies (e.g., Scrum) and a strong understanding of the software development life cycle.
Understanding of application resiliency and secure engineering practices.
Proficiency in automation and continuous delivery methods (CI/CD), including improving build, test, and deployment pipelines.
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 and outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices.

Nice To Haves

Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management.
Strong problem-solving, analytical, and communication skills.
Microservices architecture experience, including service-to-service communication, distributed systems concepts, and resilience patterns.
Experience in the banking domain.
AWS certification is a plus.

Responsibilities

Design, develop, and troubleshoot software solutions, breaking down complex technical problems and making sound engineering trade-offs.
Deliver end-to-end cloud-native applications using microservices architecture and modern engineering practices.
Use domain modeling to build business capabilities that are clear, testable, and easy to evolve.
Write secure, high-quality production code; review, debug, and improve code written by others.
Design and build scalable, resilient solutions that minimize single points of failure and support high availability.
Improve operational stability by identifying recurring issues and eliminating root causes through automation and durable fixes.
Investigate incidents promptly, resolve root causes, and implement prevention measures so issues do not recur.
Keep systems current by updating technologies, libraries, and patterns in a controlled, low-risk manner.
Enable reliable delivery by applying CI/CD and release patterns that support safe deployments and minimal downtime.
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.