Manager of Software Engineering - Analytics & Feedback Platforms

Lead multiple teams, manage day-to-day implementation activities, and set overall guidance for team output, practices and collaboration

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 Employee Platforms, 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 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. Experience leading technology teams, managing technologists, and delivering complex technology initiatives from concept through production. 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. Hands-on experience delivering system design, application development, testing, deployment, and operational stability across the full Software Development Life Cycle. Strong full-stack engineering background with expertise in backend application development and application integrations. Expert-level knowledge of one or more programming languages, with the ability to independently solve complex design, scalability, performance, and functionality challenges. Advanced understanding of Agile delivery, CI/CD, application resiliency, security, observability, and cloud-native engineering practices. Practical experience developing and deploying applications in public or private cloud environments. Proven ability to establish engineering standards, drive technical excellence, and promote software quality through code reviews, automated testing, reusable patterns, and engineering automation. Preferred qualifications, capabilities, and skills Advanced proficiency in Java, JEE, Spring, Spring Boot, REST APIs, Kafka, automated testing frameworks, integration testing, and modern engineering practices. Strong analytical and problem-solving skills, with the ability to evaluate multiple solution options and make sound technical decisions with limited oversight. Working knowledge of financial services technology environments, controls, compliance expectations, and regulatory considerations. Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field, or equivalent practical experience. Practical cloud native experience