Manager of Software Engineering - Java Full Stack, AI/ML

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

As a Manager of Software Engineering at JPMorgan Chase within the Commercial & Investment Bank, Payments Technology, 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.

Job responsibilities

• Provides guidance to immediate team of software engineers on daily tasks and activities
• 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

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. Experience managing technologists
• Proficient in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle. Experience with Full Stack Java project and good understanding of Data Engineering , AI/ML
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• In-depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience.
• 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.

Preferred qualifications, capabilities, and skills