Software Engineer III - Python / Front Office Commodities

About the role

JPMorganChase is looking for a Software Engineer III (Athena/Python) in its Commercial and Investment Banking - Precious Metals and Agriculture - Commodities Technology team. You will join an agile team that designs and delivers trusted, market-leading technology products in a secure, stable and scalable way, supporting the firm's business objectives.

Key responsibilities

• Work with Precious Metals/Agriculture Trading, Quantitative Research, Sales, Middle Office and other technology teams to gather requirements and deliver reliable solutions.
• Design, develop and maintain trading applications and systems used by the Front Office.
• Use enterprise-authorized AI coding assist tools to improve code quality, delivery speed and productivity (code generation, refactoring, unit tests, documentation), validated by peer review, automated testing and secure coding standards.
• Troubleshoot production issues in a time-sensitive environment and improve code quality, performance and system resilience.
• Review and debug code written by others and collaborate with global technology teams in an agile manner.
• Contribute to software engineering communities of practice and events on emerging technologies.

Required profile

• Formal training or certification in software engineering concepts and 3+ years of applied experience.
• Bachelor's degree in Computer Science or equivalent.
• Hands-on experience delivering system design, application development, testing and operational stability.
• Experience in performant, large-scale systems in an object-oriented or functional language such as Python or Java.
• Hands-on experience with enterprise-authorized AI-assisted development tools, able to validate and refine AI-generated outputs for correctness, performance and security.
• Preferred: experience in commodities, finance or investment banking, and willingness to learn the business domain.

Required skills

• Agile methodologies, including CI/CD, application resiliency and security.
• Full-stack development and quantitative finance knowledge.
• Responsible AI use in engineering workflows, including data sensitivity and secure handling of inputs and outputs.
• Excellent communication skills with both business users and engineers.