Lead Software Engineer - Full Stack Java
JPMorgan Chase · jpmorganchase.com
ChicagoLead / Manager5+ yrs
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The job in short
Full stack Java engineer.
JavaReactAngularSQLNoSQLMongoDBMicroservicesOracle
Details
- Found
- 20 d ago · posted 2026-10-16
- Location
- Chicago, IL
Full description
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology, 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. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• 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 evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• 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.
• 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
Required qualifications, capabilities, and skills
• Formal training or certification on software engineering concepts and 5+ years hands on Software Development Life Cycle experience
• Experience implementing solutions using Java, SQL, UI frameworks, Design patterns, microservices, Cloud native architecture, Angular/React, RESTful APIs for enterprise-scale applications.
• Experience with SQL performance tuning, JDBC, and ORM frameworks (Hibernate/JPA)
• Strong experience in various SQL and NoSQL datastores including Oracle, MongoDB
• Deep knowledge in caching technologies such as Elasticsearch, Reddis and so on
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• 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
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Proficiency in unit testing frameworks such as JUnit and Mockito for ensuring code quality.
• Deep knowledge of messaging platforms such as Apache Kafka
Preferred qualifications, capabilities, and skills
• Familiarity with DevOps practices, containerization and orchestration
• Exposure to AI systems such as Copilot, Claude
• Exposure to AWS technology stack
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