Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer Mainframe Cobol at JPMorgan Chase within the Consumer & Community Banking, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
- Implement creative software solutions, utilizing a forward-thinking approach to problem-solving and technical troubleshooting.
- Lead modernization architecture and design planning by applying advanced knowledge of COBOL, CICS, DB2, IBM MQ, and DB2 Utilities to drive target-state designs, migration patterns, and technical execution plans.
- Develop secure, high-quality production code, while also reviewing and debugging code authored by others.
- Identify opportunities for automation to enhance operational stability and efficiency of software applications and systems.
- Contribute to software engineering communities of practice, fostering exploration of new technologies.
- Develop solutions, reusable patterns, and documentation to address recurring challenges.
- Collaborate with engineering teams to identify and mitigate technical issues, offering strategies for improvement.
- Participate in technology training sessions and knowledge transfer activities.
- Assist teams in understanding the SDLC process, guide the development of non-functional requirements, and conduct thorough reviews of HLDD.
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience. In addition.
- Extensive hands on experience in mainframe technologies and tools, including Cobol, CICS, DB2, MQ messaging, DB2 Utilities, JCL, and file transfer mechanisms.
- Experience with Cloud Technologies in particular Public Cloud and AWS.
- Experience in crafting well-architected designs, application development, testing, resiliency and operational stability to utilize the capabilities of cloud computing for applications
- Advanced knowledge in one or more software, applications, and architecture
- Experience applying expertise and new methods to determine solutions for complex architecture problems in one or more technical disciplines.
- Proven experience in managing large-scale mainframe implementations and systems.
- Experience of building secure solution designs including cloud experience
- Ability to tackle design and functionality problems independently with little to no oversight
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
Preferred Qualifications, Skills, and Capabilities:
- Expertise in modernization in cloud platform from large, complex heritage ecosystem of mainframe and monoliths.
- Experience with distributed technologies and AI tools is desirable
- Experience with Micro-Services and Event-Driven architectures