As a Manager of Software Engineering at JPMorganChase within the Consumer and Community Banking's Card Technology team , you lead multiple teams and manage day-to-day implementation activities by identifying and escalating issues and ensuring your team’s work adheres to compliance standards, business requirements, and tactical best practices. You will act as a senior solution architect for our delivery control plane — the environments, pipelines, promotion controls, quality gates, and release evidence. You will translate ambiguous problems into practical architectures, validate designs through hands-on prototypes, and help teams adopt solutions with confidence.
Job responsibilities
- Provides guidance to immediate team of software engineers on daily tasks and activities, influence engineers, architects, peer leaders, and control partners across teams to align on practical, adoptable platform designs.
- Sets the overall guidance and expectations for team output, practices, and collaboration
- Leads team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes, while setting expectations for human validation, secure handling of inputs/outputs, and consistent use of reusable patterns across teams.
- 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 and support capacity unlock initiatives.
- Anticipates dependencies with other teams to deliver products and applications in line with business requirements
- Manages stakeholder relationships and the team’s work in accordance with compliance standards, service level agreements, and business requirements
- Remain hands-on at a senior engineering level by reviewing code, interpreting unfamiliar systems, validating AI-generated output, and building MVPs to de-risk major technical directions.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, demonstrated coaching and mentoring experience
- Experience leading technology projects and managing technologists
- Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams, including defining ways of working (review/validation expectations), measuring outcomes, and ensuring secure handling of data.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and governance expectations; ability to coach engineers on compliant and effective usage.
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Demonstrated breadth across the technology landscape, with the ability to assess an unfamiliar design, codebase, or production issue quickly and identify what actually matters.
Experience with code review and validation — able to read, critique, and correct both human and AI-generated code, and to build working prototypes.
Proven stakeholder engagement and relationship-building skills, with a track record of influencing peer leaders and driving alignment without direct authority.
Advanced proficiency with modern AI-assisted development — practical experience with agents, MCP, skills, prompting, RAG, and memory — applied to real engineering and governance work.
- Experience with mainframe platforms, including the release, environment, and testing constraints they introduce into a modern delivery pipeline.
Experience with Card platforms or comparable large-scale payments and transaction-processing systems.