Manager of Software Engineering

This is your chance to change the path of your career and guide multiple teams to success at one of the world's leading financial institutions.

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.

Preferred qualifications, capabilities, and skills

• 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.