About The Position

As a Software Engineer III on JPMorganChase’s Payments Common Core Services team, you will serve as an experienced member of an agile team, designing and delivering secure, stable, scalable technology products. You will implement critical technology solutions across technical areas and business functions in support of the firm’s objectives. The role includes developing and maintaining production software, creating architecture and design artifacts, troubleshooting technical issues, and using data insights to improve applications and systems. You will also use enterprise-authorized AI-assisted development tools responsibly to improve code quality, delivery speed, and productivity, validating their outputs through peer review, automated testing, and secure coding standards.

Requirements

  • Formal training or certification in software engineering concepts and at least 3 years of applied experience.
  • Hands-on practical experience in system design, application development, testing, and operational stability.
  • Experience developing, debugging, and maintaining code in a large corporate environment using Java, Spring Boot, microservices, REST API development, and one or more database querying languages.
  • Hands-on experience using enterprise-authorized AI-assisted software development tools.
  • Understanding of responsible AI use in engineering workflows and the ability to guide peers.
  • Experience with distributed databases and Jenkins CI/CD pipelines.
  • Overall knowledge of the Software Development Life Cycle.

Nice To Haves

  • Exposure to AWS cloud technologies such as EC2, EKS, RDS, S3, or Lambda.
  • Practical experience using AI-assisted developer tools and AI agents, such as Copilot, Claude Code, or equivalent, to improve engineering productivity, code quality, and knowledge acquisition.
  • Kubernetes and infrastructure-as-code experience, such as Terraform.
  • Containerization experience, such as Docker images and containers.

Responsibilities

  • Execute software design, development, and technical troubleshooting, using approaches that address complex technical problems.
  • Create secure, high-quality production code and maintain algorithms that run synchronously with appropriate systems.
  • Use enterprise-authorized AI coding-assistance tools for code generation and refactoring, unit tests, and documentation; validate outputs through peer review, automated testing, and secure coding standards.
  • Contribute learnings and reusable patterns from AI-assisted development to improve team effectiveness.
  • Use Software Development Life Cycle tools, including authorized AI-assisted development and automation capabilities, to improve the value realized through automation.
  • Produce architecture and design artifacts for complex applications and ensure software development meets design constraints.
  • Gather, analyze, synthesize, and visualize large, diverse data sets to support continuous improvement of software applications and systems.
  • Identify hidden problems and patterns in data and use insights to improve coding hygiene and system architecture.
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