Sr. Manager of Software Engineering

JPMorgan Chase & Co.•Plano, TX

About The Position

As a Senior Manager of Software Engineering at JPMorganChase, you will lead engineering teams, drive innovation, and ensure successful delivery of business-critical applications. You’ll play a key role in developing talent, building a collaborative culture, and influencing the technology roadmap, all while advancing your career in a dynamic environment.

Requirements

Formal training or certification on Software Engineering concepts and 10+ years applied experience
3+ years of managing Teams. 8+ years of industry experience
Experience leading technology projects and managing technologists.
Identify or troubleshooting application code-related issues. Take active role in code reviews to ensure solutions are aligned to pre-defined architectural specifications. Assist with design reviews by recommending ways to incorporate requirements into designs and information or data flows
Advanced understanding of agile methodologies, including CI/CD, Jules/Jenkins, application resiliency, and security.
Degree in Computer Science, Engineering, Mathematics, or a related field.
Proficiency with technologies like Java, Spring Framework, Spring WebFlux, GraphQL, Angular, Typescript, CSS, Karma, Phantoma.js, NodeJS, Maven, Oracle /postgres DB, SQL, Microservices, Public / private cloud, Apache Kafka.
Experience with security tools like Black duck, Sonar, Fortify. Infrastructure Architecture Disciplines, Authentication and authorization principles, Kerberos, Content management.
Experience with monitoring tools Dynatrace / Splunk, application management tool Servicenow, versioning tool SVN or GIT.
Demonstrated ability to grow and assess talent, manage underperformers, and build force multipliers.
Strong stakeholder management and communication skills.
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.

Nice To Haves

Experience working at code level (dedicating at least 30% of time to code commits).
Experience with UNIX/Linux, Shell Scripting, Apache Tomcat, Cassandra, data modeling, Mockito
Proven ability to drive innovation and present solutions across teams.
Experience managing dependencies and collaborating with cross-functional teams.
Ability to create stretch goals and opportunities for team members’ growth and promotion.

Responsibilities

Provide guidance to software engineers on daily tasks, team output, and best practices.
Hire and develop high-performing talent; maintain a healthy intake pipeline.
Foster team morale and encourage collaboration with other teams and partner groups.
Drive innovation by solving complex problems and promoting knowledge sharing across teams.
Own end-to-end delivery of team epics, ensuring quality and timely execution.
Manage stakeholder relationships, including Product Managers, Architecture, and Delivery teams.
Build a culture of diversity, inclusion, and respect, prioritizing opportunities for growth and advancement.
Identify and address bottlenecks to drive efficiency and improve developer experience.
Manage dependencies and build strong relationships with upstream and downstream partners.
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.