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Bring your Engineering skills and lead and manage multiple technical teams and move financial technologies forward.\nAs 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.\nJob responsibilities\n Provides guidance to immediate team of software engineers on daily tasks and activities\nSets the overall guidance and expectations for team output, practices, and collaboration\nAnticipates dependencies with other teams to deliver products and applications in line with business requirements\nManages stakeholder relationships and the team’s work in accordance with compliance standards, service level agreements, and business requirements\nCreates a culture of opportunity, inclusion, and respect for team members and prioritizes diverse representation\nSets 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.\nApplies 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.\nRequired qualifications, capabilities, and skills\n Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, demonstrated coaching and mentoring experience \nExperience leading technology projects\nExperience managing technologists\nProficient in automation and continuous delivery methods\nProficient in all aspects of the Software Development Life Cycle\nAdvanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security\nIn-depth knowledge of the financial services industry and their IT systems\nPractical cloud native experience\nExperience working at code level\nExperience 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.\nStrong 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.\nPreferred qualifications, capabilities, and skills\n Experience working with Java Springboot, Python, PySpark, MongoDB, Oracle, Unix\nExperience working with AI - 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