Sr. Lead Software Engineer- Full Stack/Java/Python/AWS/Rea

JPMorganChase•Jersey City, NJ

About The Position

As a Sr. Lead Software Engineer on JPMorgan Chase's Consumer and Community Banking-Wealth team, you will contribute to an agile team building and enhancing trusted, market-leading technology products. You will deliver critical technology solutions across multiple technical areas in support of business objectives, ensuring they are secure, stable, and scalable. The role focuses on delivering cloud-native, microservices-based applications using modern technologies and industry best practices. You will develop high-quality business products through domain modeling, write and review production code, and build scalable, secure, reliable systems. You will also help drive the responsible adoption and governance of approved AI-assisted engineering practices, including standards for validating AI outputs and improving code quality, delivery speed, and operational outcomes.

Requirements

Formal training or certification in software engineering concepts and at least 5 years of applied experience.
Proficiency in back-end technologies such as Java, Spring Boot, or Node.js, and experience building microservices-based applications.
For full-stack work, proficiency in front-end technologies such as HTML, CSS, JavaScript, TypeScript, React, or Angular.
Ability to independently solve design and functionality challenges with minimal supervision.
Experience with cloud platforms such as AWS, Azure, or GCP; distributed systems; and web technologies including RESTful APIs, web services, WebSockets, and JSON.
Hands-on experience designing and building scalable applications using SQL and NoSQL databases.
Proficiency across the software development life cycle (SDLC) and experience with Agile methodologies such as Scrum.
Experience leading effective use of enterprise-authorized AI-assisted software development tools for tasks such as coding, code review, test acceleration, and troubleshooting, and setting team expectations for validating AI outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations.
Experience coaching senior engineers or leads on compliant AI usage patterns and controls.
Understanding of application resiliency and security principles.
Proficiency in automation and continuous integration and delivery (CI/CD) methods.
Demonstrated proficiency in software applications and technical processes within a technical discipline such as cloud, artificial intelligence, machine learning, or mobile.

Nice To Haves

Strong presentation, negotiation, mentoring, and stakeholder management skills.
Strong problem-solving, analytical, and communication skills.
Experience developing, testing, and maintaining software in Python, including writing clear, reusable code, troubleshooting issues, and using appropriate libraries and frameworks to build reliable solutions.
Ability to drive broader impact by sharing and contributing best practices.
Experience in the banking domain.
AWS certification.

Responsibilities

Develop creative software solutions using sound design, development, and troubleshooting practices to solve complex technical problems.
Drive adoption and governance of approved AI-assisted engineering practices across teams, with measurable validation standards for secure coding, peer review, and automated testing.
Promote reuse of proven patterns and automation within the SDLC/TLM toolchain.
Use tools across the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized through automation at scale.
Deliver end-to-end cloud-native, microservices-based applications using modern technologies and industry best practices.
Apply domain modeling to build high-quality business products and structure software for clarity, testability, and evolution.
Write secure, high-quality production code; review and debug code written by others.
Identify opportunities to automate recurring remediation, investigate and resolve issues promptly, and prevent recurring issues to improve operational stability.
Design and build scalable, secure, and reliable systems using modern architectural patterns that avoid single points of failure, enable zero-downtime releases, and optimize data performance.
Keep systems current by adopting relevant technologies, patterns, and practices.
Contribute to Software Engineering communities of practice to share awareness and encourage adoption.
Foster a team culture grounded in diversity, opportunity, inclusion, and respect.