Back-end Java Software Engineer III

JPMorganChase•Wilmington, NC

About The Position

As a Software Engineer III at JPMorgan Chase within the Corporate Sector, you will join an agile team enhancing, designing, and delivering software components for the firm’s technology products in a secure, stable, and scalable way. You will execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while continuing to develop your skills and experience.

Requirements

  • Formal training or certification in software engineering concepts and at least 3 years of applied experience.
  • Proficiency in back-end technologies such as Java, Spring Boot, and microservices.
  • Experience building microservices and RESTful API-based applications.
  • Experience with automation testing using Cucumber and Karate.
  • Hands-on experience using enterprise-authorized AI-assisted software development tools, with the ability to critically evaluate and validate AI-generated outputs.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations.
  • Experience across the full software development life cycle.
  • Ability to independently solve design and functionality challenges with minimal supervision.
  • Experience with cloud platforms such as AWS, Azure, or GCP; distributed systems; and web technologies, including RESTful APIs, web services, WebSockets, and JSON.

Nice To Haves

  • Hands-on experience with front-end technologies such as HTML, CSS, JavaScript, TypeScript, React, or Angular.
  • Hands-on experience with AWS.
  • Experience with Copilot and other AI platforms.
  • Hands-on experience with IBM ODM or DROOLS.

Responsibilities

  • Execute standard software solution design, development, and technical troubleshooting.
  • Write secure, high-quality code using at least one programming language, with limited guidance.
  • Use enterprise-authorized AI coding-assistance tools to improve code quality, delivery speed, and productivity, validating outputs through peer review, automated testing, and secure coding standards.
  • Design, develop, code, and troubleshoot with consideration of upstream and downstream systems and technical implications.
  • Use software development lifecycle tools, including authorized AI-assisted development and automation capabilities, to improve the value of automation.
  • Break down solutions and solve technical problems of basic complexity through technical troubleshooting.
  • Analyze large and diverse data sets to identify problems and contribute to decisions that support secure, stable application development.
  • Learn and apply system processes, methodologies, and skills for developing secure, stable code and systems.
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