Lead Software Engineer
Summary
Lead a team building secure, cloud-native banking microservices in Java/Spring Boot, using AI-assisted tools to deliver scalable, zero-downtime systems for consumer banking.
Carry out critical tech solutions across multiple technical areas as an integral part of an agile team.
As a Lead Software Engineer at JPMorgan Chase within Consumer and community banking technology team, you are an integral part of an agile team that works to enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way.
Job Responsibilities
- Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond routine or conventional approaches to build solutions or break down technical problems.
- Deliver end-to-end solutions in the form of cloud-native, microservices-based applications, leveraging the latest technologies and best industry practices.
- Use domain modeling techniques to build best-in-class business products, structuring software for clarity, testability, and evolution.
- Develops secure high-quality production code, and reviews and debugs code written by others.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies.
- Adds to team culture of diversity, opportunity, inclusion, and respect.
- Promptly investigate and resolve issues, ensuring they do not resurface.
- Continuously update technologies and patterns to keep systems current.
- Design and build solutions that avoid single points of failure using scalable architectural patterns.
- Design and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.
- 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
- Formal training or certification on software engineering concepts and 5+ years of hands-on experience in software engineering, including system design, application development, testing, and operational support.
- Proficiency in back-end technologies (e.g., Java, Springboot,) with experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g., HTML, CSS, JavaScript, Typescript, React, Angular).
- Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON.
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
- Strong proficiency in Java and related frameworks (Spring, Spring Boot, Hibernate).
- Experience with front-end technologies: HTML5, CSS3, JavaScript, and modern frameworks (Angular, React).
- Familiarity with database technologies (SQL, MySQL, PostgreSQL).
- Experience with version control systems (Git).
- Hands on experience with AI tools is a must.
- 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
- Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management.
- Strong problem-solving, analytical, and communication skills.
- Ability to drive broader impact by sharing and contributing best practices.
- Experience in the banking domain.
- AWS certification.
- Understanding of RESTful API design and integration.