Manager of Software Engineering

JPMorgan Chase & Co.; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Manager of Software Engineering to lead multiple teams within Card Technology. You will guide day-to-day engineering activities, ensure compliance with standards, and translate complex problems into practical architectures.

You will stay hands-on, review code, and build MVPs to de-risk major directions. The role emphasizes AI-assisted development, SDLC automation, and cross-team collaboration to accelerate delivery while maintaining security and governance

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience, plus coaching/mentoring experience.
• Experience leading technology projects and managing technologists.
• Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools, including defining ways of working, measuring outcomes, and ensuring secure data handling.
• Understanding of responsible AI use in engineering workflows, including data sensitivity, resiliency and governance expectations; ability to coach engineers.
• Proficient in all aspects of the Software Development Life Cycle.
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• Demonstrated ability to assess unfamiliar design/code quickly and identify what matters.
• Experience with code review and validation of human and AI-generated code, and building working prototypes.
• Proven stakeholder engagement and relationship-building skills.
• Advanced proficiency with modern AI-assisted development—agents, MCP, prompting, RAG, and memory.

Responsibilities

• Guides the software engineering team on daily tasks and aligns multiple teams on practical platform designs.
• Sets guidance and expectations for team output and collaboration across teams.
• Drives adoption of AI-assisted development and SDLC/TLM automation with human validation and security.
• Utilizes the SDLC toolchain to improve automation value and capacity unlock initiatives.
• Anticipates dependencies to deliver products meeting business requirements.
• Manages stakeholder relationships within compliance and SLA requirements.
• Stays hands-on at a senior level by reviewing code, validating AI output, and building MVPs.

Skills

Leadership & mentoring

AI-assisted development

CI/CD pipelines

Software architecture

Code review

Stakeholder management

Agile methodologies

Problem solving

Security & resiliency

Compliance awareness

Education

Bachelor's degree in Computer Science or related field

Tools

CI/CD tooling

AI governance tooling

Mainframe familiarity

Job description

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.