Software Engineer II

About the Role

As a Software Engineer II within the Commercial & Investment Bank- Payments Technology team at JPMorganChase, you will be part of an agile team enhancing, designing, and delivering software components for state-of-the-art technology products in a secure, stable, and scalable manner. You will execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system.

Key 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 (e.g., code generation/refactoring, unit test creation, documentation), 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 (SDLC) toolchain, including enterprise-authorized AI-assisted development and automation capabilities.
• Applies technical troubleshooting to solve technical problems of basic complexity.
• Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making for secure, stable application development.
• Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems.

Requirements & Tech Stack

• Hands-on practical experience in Databricks, AI/ML, Python, AWS, ETL, SQL.
• 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 (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.

Qualifications

• Formal training or certification on software engineering concepts and 2+ years applied experience.
• Java developer experience in enterprise application development.
• At least two years experience in Java 17+.
• 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).