Software Engineer II

About the Role

As a Software Engineer II at JPMorganChase, you are part of an Employee Platforms team focused on enhancing, designing, and delivering software components for the firm's technology products in a secure, stable, and scalable manner. You will execute software solutions through design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining skills for career growth.

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 within the work environment to improve code quality, delivery speed, and productivity, 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 (SDLC) toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve value realized by automation.
• Applies technical troubleshooting to break down 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.

Requirements & Tech Stack

• Formal training or certification on software engineering concepts and 2+ years applied experience.
• Hands-on practical experience in system design, application development, testing, and operational stability.
• Develop, debug, and maintain code in a large corporate environment using one or more modern programming languages and database querying languages.
• Use enterprise-authorized, AI-assisted software development tools (for example, for coding, testing, troubleshooting, or documentation) while critically evaluating and validating 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

• Exposure to AI technologies.
• Knowledge on Cloud.