Lead Software Engineer - Python, Credit Trading Technology

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As a Lead Software Engineer at JPMorgan

Chase within the Commercial & Investment Bank - Credit Trading Technology team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

• Executes creative software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Builds and supports AI-enabled systems to expand electronic trading capabilities, including scalable AI platforms and modernization of existing systems using approved AI tooling
• Partners directly with Credit Sales and Trading and Product teams to understand business strategy and deliver impactful technical solutions
• Architects and builds new systems hands-on using modern engineering practices and develops secure, high-quality production code while reviewing and debugging code written by others
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve operational stability and partners with support teams to ensure production reliability and timely issue resolution
• Leads evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical capabilities, and applicability within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and adoption of new and leading-edge technologies
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.

• 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.

• Formal training or certification on software engineering concepts and 5+ years of applied experience
• Advanced hands‑on experience with Python and delivering system design, application development, testing, and operational stability
• Hands‑on experience with artificial intelligence components and their application within modern technology stacks
• Practical cloud-native experience, including foundational knowledge of AWS services and cloud engineering practices
• Proficiency in automation and continuous delivery methods and all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies, CI/CD, application resiliency, and security
• Demonstrated technical proficiency across modern software engineering disciplines such as cloud, artificial intelligence, and machine learning
• Experience working with business and product partners to translate requirements into scalable technical solutions
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness,…