JOB DESCRIPTION
Job Description
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 JPMorgan Chase within the Asset and Wealth Management, 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
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Provides guidance to immediate team of software engineers on daily tasks and activities
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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
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.
Manages stakeholder relationships and the team's work in accordance with compliance standards, service level agreements, and business requirements
Required qualifications, capabilities, and skills
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Formal training or certification on software engineering concepts and 5+ years applied experience
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Having proficiency Java language
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Hands on experience in Microservices, RESTful webservices development in Java (SpringBoot or equivalent framework).
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Good knowledge in relational databases and SQL
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In depth knowledge of Cloud Native Architecture, Microservice Architecture, and related stacks
Exceptional communication and interpersonal skills - including negotiation, facilitation, and consensus building skills; ability to influence and persuade, without direct control.
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.
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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.
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Mentoring/coaching Senior staff engineers and other Engineers.
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Focus on reusability, frameworks, patterns, and configurations tools for faster development.
Preferred qualifications, capabilities, and skills
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