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Salary
$29k – $87k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 10+ years exp
Overview
Company
Impact
Profile match
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.

Join us to shape innovative technology products and advance your career in a dynamic environment. Experience the impact and growth opportunities of leading a high-performing team.

As a Lead Software Engineer at JPMorgan Chase within the Chief Technology Office team, you deliver trusted, market-leading technology products in a secure, stable, and scalable way. You are responsible for critical solutions across multiple technical areas supporting business objectives. You work collaboratively to enhance and build products, contributing to a culture of opportunity and growth. We value your technical leadership and commitment to excellence.

Job responsibilities

  • Execute creative software solutions, design, development, and technical troubleshooting
  • Deliver end-to-end solutions using cloud-native, microservices-based applications
  • Use domain modeling techniques to build business products
  • Develop secure, high-quality production code and review code written by others
  • Identify opportunities to eliminate or automate remediation of recurring issues
  • Lead communities of practice across Software Engineering and promptly investigate and resolve issues
  • Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
  • Continuously update technologies and patterns
  • Design and build solutions that avoid single points of failure
  • Design and build scalable, secure, and reliable solutions using modern architectural patterns

Required qualifications, capabilities and skills

  • Formal training or certification on software engineering concepts and 10+ years applied experience
  • Proficiency with modern front-end stacks: JavaScript or Typescript, using React or frameworks
  • Ability to independently solve design and functionality challenges with minimal supervision
  • Understanding of modern design patterns used in JavaScript
  • Knowledge and experience working with HTML5, CSS, and pre-compilers like Sass and LESS
  • Experience with agile development methodologies and understanding of the software development life cycle
  • Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations
  • Proficient in all aspects of the Software Development Life Cycle
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Preferred qualifications, capabilities and skills

  • Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management
  • Strong problem-solving, analytical, and communication skills
  • Ability to drive broader impact by sharing and contributing best practices
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