at J.P. Morgan
Bulge Bracket Investment BanksPosted 8 days ago
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**Lead Software Engineer - Java / Post Trade Technology:** Champion innovative, secure, and scalable Java solutions in Jersey City, NJ. As a seasoned Lead, you'll drive software development lifecycle, mentor team adoption of AI-assisted engineering practices, and collaborate across business functions. requirements include 8+ years' experience, expertise in Core Java, proficiency in NoSQL, Kafka, Node/ReactJS, and demonstrated leadership in AI-assisted software development. In-depth financial services industry knowledge and cloud experience are preferred.
- Compensation
- Not specified
- City
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- Country
- United States
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Full Job Description
Location: Jersey City, NJ, United States
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 Commercial and Investment bank, 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 firms business objectives.
Job responsibilities
As a Lead Software Engineer at JPMorgan Chase within the Commercial and Investment bank, 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 firms 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 breakdown technical problems
- Develops secure and high-quality production code, and reviews and debugs code written by others
- 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.
- 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
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 8+ years applied experience
- Expertise in Core Java, data structures, algorithms, industry wide design patterns and infrastructure architecture disciplines
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Demonstrate experience in messaging platforms (Apache Kafka or equivalent), No SQL DB's (like Mongo DB & Redis)
- Exposure to web technologies like Node/ReactJS and electron framework
- 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
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- In-depth knowledge of the financial services industry and their IT systems
- Practical cloud native experience
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies
- Exposure to cloud technologies
- Exposure to Generative AI
