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Full Stack Lead Software Engineer

Job in Jersey City, Hudson County, New Jersey, 07390, USA
Listing for: JPMorgan Chase & Co.
Full Time position
Listed on 2026-10-26
Job specializations:
  • Software Development
    Full Stack Developer, Software Engineer, Cloud Engineer - Software, DevOps
Salary/Wage Range or Industry Benchmark: 140000 - 210000 USD Yearly USD 140000.00 210000.00 YEAR
Job Description & How to Apply Below

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, 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.

Job Responsibilities
  • 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.
  • 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.
  • 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.
  • Promptly investigate and resolve issues, ensuring they do not resurface. Continuously update technologies and patterns to keep systems current.
  • Design and build solutions that avoid single points of failure using scalable architectural patterns.
  • Design and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.
Required qualifications, capabilities, and skills
  • 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.
  • Proficiency in back-end technologies (e.g., Java, Springboot, Node.js ) with experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g. JavaScript, Typescript, React, Angular).
  • Demonstrated ability to independently solve design and functionality challenges with minimal supervision.
  • Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, Web Sockets, and JSON.
  • 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.

  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of…

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