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Salary
$121k – $244k per year (Estimated)
Location
In office (Chicago)
Seniority
Middle · 3+ years exp
Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III at JPMorgan Chase within the Commercial and Investment Bank, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

  • Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
  • Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
  • Design and build AWS and private cloud full-stack JAVA solutions for CIB use cases
  • Design and maintain master data model for multiple key domains
  • Design and build scalable ingestion and data distribution pipelines, develop APIs
  • Develop end-to-end CI/CD ML pipelines to deploy the knowledge graphs and associated processes
  • Build infrastructure as code processes to have a fully resilient and performant environment on AWS
  • Collaborate across the Commercial Bank Data Platform team to leverage existing data assets in the knowledge graph and to drive the creation of additional data assets
  • Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
  • 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.
  • Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 3+ years applied experience
  • Hands-on practical experience in system design, application development, testing, and operational stability
  • Experience in Java Full Stack and advanced SQL development
  • Expertise with Java, Python, JavaScript, REACT, Spring, and related software engineering platforms/frameworks
  • Experience with AWS environments including EC2, ASG, Lambda, EKS, RDS, Code Deploy, and others
  • Experience developing APIs leveraging different back-end data stores (RDS, Graph, Dynamo, etc.)
  • Experience working with end-to-end, fully automated CI/CD pipelines using frameworks like Jules, Spinnaker, Code Deploy, etc.
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
  • Overall knowledge of the Software Development Life Cycle
  • Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security

Preferred qualifications, capabilities, and skills

  • Familiarity with modern front-end technologies
  • Exposure to cloud technologies
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