Lead Software Engineer - Java Backend Engineer

JPMorgan Chase JPMorgan Chase · Banking · NY · Consumer & Community Banking

Lead Software Engineer role focused on backend Java development within a financial services technology team. The role emphasizes enhancing, building, and delivering technology products securely and scalably. A key aspect is driving the adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, with a strong focus on responsible AI use, validation of AI outputs, and coaching engineers on safe adoption.

What you'd actually do

  1. Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
  2. Develops secure and high-quality production code, and reviews and debugs code written by others
  3. 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.
  4. 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.
  5. Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems

Skills

Required

  • Java 17+
  • Java 17+ distributed application development
  • REST
  • micro services
  • Spring Boot
  • database technologies (e.g. Cassandra, Cockroach)
  • Behavior Driven Development using Cucumber
  • agile methodologies
  • CI/CD
  • Application Resiliency
  • Security

Nice to have

  • deploying applications in AWS
  • message bus technologies such as Kafka or IBM MQ
  • automation using Maven
  • Continual Integration in Jenkins

What the JD emphasized

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • 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 inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices