Python Software Engineer III

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. At JPMorganChase, you'll collaborate with a diverse, agile team to deliver trusted, market-leading technology products in a secure, stable, and scalable way. We value your expertise and encourage you to push the boundaries of what's possible. Join us and be part of a culture that celebrates innovation, inclusion, and continuous learning.

As a Software Engineer III at JPMorganChase within Corporate Technology, you will serve as a seasoned member of an agile team, designing and delivering trusted, market-leading technology products in a secure, stable, and scalable way. You will be 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

• Execute software solutions across design, development, and technical troubleshooting, thinking beyond routine approaches to build innovative solutions and break down complex technical problems
• Create secure, high-quality production code and maintain algorithms that operate synchronously with appropriate systems
• Produce architecture and design artifacts for complex applications, ensuring design constraints are met throughout software code development
• Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Proactively identify hidden problems and patterns in data, using insights to drive improvements in coding hygiene and system architecture
• Contribute to software engineering communities of practice and participate in events exploring new and emerging technologies
• Foster a team culture of diversity, opportunity, inclusion, and respect through active collaboration and engagement
• 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
• 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

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and proficient applied experience
• Hands-on practical experience in system design, application development, testing, and operational stability
• Proficiency in coding in one or more programming languages
• Experience developing, debugging, and maintaining code in a large-scale environment using one or more modern programming languages and database querying languages
• Overall knowledge of the Software Development Life Cycle
• Solid understanding of agile methodologies such as continuous integration/continuous delivery, application resiliency, and security
• Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, Databricks, PySpark, artificial intelligence, machine learning, mobile, etc.)
• 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

Preferred qualifications, capabilities, and skills

• Familiarity with modern front-end technologies and evolving user interface frameworks
• Exposure to cloud technologies including AWS, Databricks, and agentic AI solutions
• Knowledge of industry-wide technology trends and best practices across disciplines such as artificial intelligence, machine learning, and mobile development