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Lead Software Engineer - Mainframe role at JPMorgan Chase, Jersey City, focus on mainframe systems, AI integration, leadership responsibilities.
Seeking experienced leader with deep mainframe skills and AI engineering expertise to manage large-scale financial services systems.
Intro
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 JPMorganChase within the Enterprise 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.
As a key overseer of the implementation and management of large-scale mainframe systems within the financial services industry. This role is pivotal in ensuring the efficient operation and management of systems housing millions of Prime Brokerage and Wealth Management client account reference data. The ideal candidate will have a strong background in mainframe technologies and tools, along with experience in distributed technologies and AI tools.
Job responsibilities
- Lead the implementation and management of mainframe systems, ensuring high performance, reliability, and scalability.
- Utilize expertise in mainframe technologies such as Cobol, CICS, DB2, VSAM, MQ messaging, Stored procedures, DB2 Utilities, JCL, ChangeMan, NDM, and other file transfer mechanisms to maintain and enhance applications.
- Provide leadership, guidance, and support to ensure team success and development.
- Collaborate with cross-functional teams to integrate distributed technologies and AI tools into mainframe systems, enhancing functionality and efficiency.
- 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.
- Ensure compliance with industry standards and best practices in mainframe technology and data management.
- Develop and implement strategies for system optimization, data integrity, and security.
- Monitor system performance and troubleshoot issues to ensure uninterrupted service.
- Communicate effectively with stakeholders, providing updates on project progress, challenges, and solutions.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Experience in the financial services industry, managing large-scale mainframe applications.
- Extensive hands on experience in mainframe technologies and tools, including Cobol, CICS, DB2, VSAM, MQ messaging, Stored procedures, DB2 Utilities, JCL, ChangeMan, NDM, and file transfer mechanisms.
- 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 practicesDemonstrated 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.
- Proven experience in managing large-scale mainframe implementations and systems.
- Strong leadership skills with experience managing global teams
- Excellent problem-solving skills and the ability to work under pressure.
- Strong communication and interpersonal skills.
Preferred qualifications, capabilities, and skills
- Experience with distributed technologies and AI tools is highly desirable