Develops secure, scalable software within an agile Payments Technology team. Responsibilities include designing, coding, troubleshooting, testing, and maintaining Python applications; analyzing data; applying SDLC practices; and using AI-assisted development tools responsibly. Preferred experience includes full-stack Python development, microservices, AWS deployment using EKS, ECS, and EC2, Terraform automation, and Oracle or PostgreSQL databases.
You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you.
As a Software Engineer II at JPMorganChase within the Commercial & Investment Bank- Payments Technology team, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.
Job responsibilities
As a Software Engineer II at JPMorganChase within the Commercial & Investment Bank- Payments Technology team, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.
Job responsibilities
- Executes standard software solution, design, development, and technical troubleshooting
- Writes secure and high-quality code using the syntax of at least one programming language with limited guidance
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
- Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
- 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
- Applies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity
- 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
- Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems
Required qualifications, capabilities, and skills
- A. Formal training or certification on software engineering concepts and 2+ years applied experience
- Hands-on practical experience in Python and AI/ML
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
- 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 across the whole Software Development Life Cycle
- Exposure to agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
- Full stack Python developer experience in enterprise application development
- Strong experience in SDLC delivery in Agile methodologies
- Experience developing microservices, packaged into AWS Elastic Kubernetes Service and/or Elastic Container Service, and deployed to EC2 instances
- Experience writing Terraform scripts and deploying in AWS production environment
- Experience in at least one relational database management system (preferably Oracle or PostgreSQL)
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