
Lead Software Engineer - Full Stack Java
JPMC · Chicago, IL, United States
Strong hiring record · median 28 days open
Hiring signal
Actively hiring
Still listed on the employer's own board · publishes a salary range · How we score
All reasons
- The same description appears on 7 of this employer's postings
In its favour
- Still listed on the employer's own board
- Publishes a salary range
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
Skills
- Java
- SQL
- Angular
- React
- JDBC
- Hibernate
- JPA
- Oracle Database
- MongoDB
- Elasticsearch
- JUnit
- Mockito
- Kafka
- GitHub Copilot
- Anthropic Claude
- AWS
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