Python Software Engineer III

Overview

As a Software Engineer III in the FX Options team at JPMorganChase, you design and deliver trusted technology products in a secure, scalable way within an agile environment. You work on critical solutions across multiple domains to support business objectives, balancing performance and security. You produce architecture and high-quality production code, and analyze data to drive continuous improvement. You will responsibly leverage AI-assisted development tools and contribute to a diverse, inclusive team culture.

Responsibilities

• Execute software solutions, design and develop, and troubleshoot complex problems beyond routine approaches
• Create secure, high-quality production code and maintain algorithms
• Produce architecture and design artifacts for complex applications ensuring constraints are met
• Analyze large data sets to support continual improvement of software and systems
• Identify hidden data patterns to drive improvements in coding hygiene and system architecture
• Contribute to software engineering communities of practice and events
• Support team culture of diversity, inclusion, and respect
• Leverage enterprise-authorized AI coding assist tools to improve code quality, delivery speed, and productivity with peer review and secure coding standards
• Apply SDLC tools and AI-assisted development to enhance automation value

Key requirements

• Formal training or certification on software engineering concepts and proficient applied experience
• Hands-on experience in system design, application development, testing, and operational stability
• Proficiency in coding in one or more languages
• Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming languages and database querying languages
• Knowledge of the Software Development Life Cycle
• Understanding of agile methodologies including CI/CD, Application Resiliency, and Security
• Experience with enterprise-authorized AI-assisted software development tools and ability to critically evaluate outputs
• Understanding of responsible AI use in engineering workflows, data sensitivity, secure handling, resiliency and security
• Python (preferred)
• object-oriented databases
• cloud technologies
• enterprise-authorized AI-assisted development tools
• CI/CD
• secure coding practices

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