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JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

Are you ready to make a real impact in cloud financial management technology? At JPMorganChase, you’ll collaborate with talented teams to deliver secure, scalable, and market-leading products. Here, you can push the boundaries of what’s possible while growing your skills and advancing your career. We value creativity, innovation, and a passion for technology. Join us and be part of a team where your contributions matter.

Job Summary:

As a Lead Software Engineer in the Cloud Financial Management technology team, you will play a key role in designing and delivering trusted technology solutions. You will work within an agile environment, collaborating with diverse teams to support the firm’s business objectives. Your expertise will help drive technical excellence and operational stability. You will foster a culture of innovation and continuous improvement. Together, we’ll build solutions that make a difference.

Job Responsibilities:

  • Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond conventional approaches to solve complex problems.
  • Develop secure, high-quality production code, and review and debug code written by others.
  • Drive 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.
  • Apply 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.
  • Identify opportunities to eliminate or automate remediation of recurring issues to enhance operational stability.
  • Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and applicability for integration.
  • Collaborate with cross-functional teams to deliver solutions aligned with business goals.
  • Promote best practices in software engineering, security, and resiliency.
  • Mentor and support team members in their professional development.

Required Qualifications, Capabilities, and Skills:

  • Formal training or certification on software engineering concepts and applied experience as required by local country guidance.
  • Hands-on experience delivering system design, application development, testing, and operational stability.
  • Advanced proficiency in one or more programming languages: Java, Python, Node.js, React, SQL.
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
  • Proficiency in all aspects of the Software Development Life Cycle.
  • Advanced understanding of agile methodologies such as CI/CD, application resiliency, and security.
  • In-depth knowledge of the financial services industry and IT systems.
  • Practical cloud native experience.

Preferred Qualifications, Capabilities, and Skills:

  • Experience leading teams in a large, complex organization.
  • Familiarity with modern cloud technologies and deployment practices.
  • Experience mentoring and coaching engineers.
  • Knowledge of industry-wide technology trends and best practices.
  • Experience with financial management platforms or related domains.
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