Lead Software Engineer - Python Full Stack, AI/ML

Company: JPMC Candidate Experience page

Location: Mumbai, Maharashtra, India

Type: Full-time

Posted: 2026-06-29

About this role

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank, 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 conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

  • Executes creative software solutions, design, development, and technical troubleshooting, thinking beyond routine or conventional approaches to build solutions or break down technical problems.
  • Delivers end-to-end solutions in the form of cloud-native, microservices-based applications, leveraging the latest technologies and best industry practices.
  • Uses domain modeling techniques to build best-in-class business products, structuring software for clarity, testability, and evolution.
  • Develops secure high-quality production code, and reviews and debugs code written by others.
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
  • Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies • Adds to team culture of diversity, opportunity, inclusion, and respect. Investigates and resolve issues, ensuring they do not resurface.
  • Designs and build solutions that avoid single points of failure using scalable architectural patterns. Designs and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work env...

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