About the role
Lead Software Engineer - Full Stack
Chicago, IL, United States
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Job Information
Job Identification
210734363
Job Category
Software Engineering
Business Unit
Corporate Sector
Posting Date
09/23/2026, 10:03 AM
Locations
10 S Dearborn St, Chicago, IL, 60603, US
Job Schedule
Full time
Job Shift
Day
Base Pay/Salary
Chicago,IL $137,750.00-$185,000.00
Job 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
Minimum requirements
- 5+ years SDLC experience with formal software engineering training; expertise in Java, SQL, UI frameworks, microservices, cloud-native, Angular/React, RESTful APIs
- Strong skills in SQL/NoSQL databases (Oracle, MongoDB), SQL tuning, ORM (Hibernate/JPA), caching (Elasticsearch, Redis), and messaging platforms (Kafka)
- Proven leadership in AI-assisted development tools, responsible AI practices, agile methodologies, and unit testing frameworks (JUnit, Mockito)
This listing was parsed by AI and may not be complete. Check the official posting on JPMorganChase's site for the most accurate information.