Lead Software Engineer - Python, Credit Trading Technology

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorganChase 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. Job responsibilities 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. Required qualifications, capabilities, and skills 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, performance, and security. Strong 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 coaching engineers on safe, compliant adoption within delivery practices Strong communication skills with the ability to collaborate effectively across technical, Product, and business team Preferred qualifications, capabilities, and skills Experience building scalable AI platforms for trading or financial services Experience modernizing existing systems using AI-assisted engineering tools Experience supporting electronic trading technology or other high-performance financial systems Knowledge of Credit Markets, Sales and Trading, or related financial markets technology Experience with AWS-based architectures in production environments