Java Aws Lead Software Engineer

JPMorgan Chase JPMorgan Chase · Banking · New York, NY +1 · Consumer & Community Banking

Lead Software Engineer for Consumer and Community Banking Connected Commerce team, responsible for enhancing, building, and delivering technology products. The role involves driving team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, while also setting up monitoring and reliability for infrastructure and models. Requires strong Java and AWS skills, with experience in system design, application development, and leading software engineers.

What you'd actually do

  1. 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.
  2. 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.
  3. Sets up monitoring and reliability for both infrastructure and models (drift detection, model accuracy) using Prometheus/Grafana.
  4. Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications.
  5. Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development.

Skills

Required

  • Java
  • Spring Boot
  • Spring Cloud
  • AWS
  • system design
  • application development
  • testing
  • operational stability
  • agile methodologies
  • CI/CD
  • Application Resiliency
  • Security
  • Prometheus
  • Grafana
  • Splunk
  • Dynatrace
  • Postman

Nice to have

  • architecting and delivering highly scalable, resilient, and stable systems on public cloud platforms
  • event-driven messaging and streaming technologies (e.g., Kafka)
  • NoSQL databases
  • relational databases
  • cloud-native API/microservice development
  • Jira
  • Confluence
  • IntelliJ IDEA
  • Maven
  • Git
  • Jenkins
  • Sonar
  • Artifactory
  • AI-powered code assistants

What the JD emphasized

  • 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