Lead Software Engineer - Quant Developer

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As a Lead Software Engineer at JPMorgan

Chase's Asset and Wealth Management team , you are an integral part of an agile team that works to enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for delivering critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

• Execute creative software solutions, design, development, and technical troubleshooting—thinking beyond routine or conventional approaches to build solutions or break down technical problems.
• Deliver end-to-end solutions in the form of cloud-native, microservices-based applications, leveraging the latest technologies and best industry practices.
• Use domain modeling techniques to build best-in-class business products, structuring software for clarity, testability, and evolution.
• Develop secure, high-quality production code; review and debug code written by others.
• Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
• Lead communities of practice across Software Engineering to drive awareness and adoption of new and leading-edge technologies (including AI-enabled software delivery approaches).
• Add to team culture of diversity, opportunity, inclusion, and respect.
• Promptly investigate and resolve issues, ensuring they do not resurface.
• Continuously update technologies and patterns to keep systems current.
• Design and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that enable zero-downtime releases and optimize data performance.
• Engineer and operationalize AI-enabled capabilities (e.g., agentic workflows, tool use, orchestration, evaluation/guardrails) to improve developer productivity and/or product functionality.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• 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.

• Formal training or certification on software engineering concepts and 5+ years of hands-on experience in software engineering, including system design, application development, testing, and operational support.
• Strong proficiency in back-end development with Python and Java, with experience building microservices-based applications and APIs (e.g., RESTful services, JSON).
• Strong experience building on AWS (or comparable cloud), including designing, deploying, and operating distributed, cloud-native systems.
• Experience with distributed systems and web technologies (e.g., RESTful APIs and web services, Web Sockets).
• Hands-on experience designing and building scalable applications using SQL and No
  
  SQL databases.
• Experience with agile development methodologies (e.g., Scrum) and an understanding of the software development life cycle.
• Understanding of application resiliency and designing for reliability/availability.
• Proficient in all aspects of the Software Development Life…