This role is a challenge with big impact, but you were made for this. Bring your Engineering skills and lead and manage multiple technical teams and move financial technologies forward.
As a Manager of Software Engineering at JPMorgan Chase within the Corporate - Data and Analytics team, where you will 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
- 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
- Creates a culture of opportunity, inclusion, and respect for team members and prioritizes diverse representation
- Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets.
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
- 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 working at code level
- Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns.
Preferred qualifications, capabilities, and skills
- Experience working with Java Springboot, Python, PiSpark, Mongodb, Oracle, Unix
- Experience working with AI – generative or agentic and using them in design and coding.