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 Pre-Trade 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

• Execute 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.
• Build and support AI-native systems to expand our eTrading capabilities, including the development of scalable AI platforms for trading and the modernization of incumbent systems with AI tooling.
• Engage directly with Credit Sales and Trading business partners to understand their strategy and establish technical solutions in partnership with Product teams.
• Architect and build new systems hands-on, leveraging AI-assisted coding and modern engineering practices.
• Develop secure, high-quality production code, and review and debug code written by others.
• Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability and continually enhance system stability KPIs.
• Partner with L1 support teams to provide direct support for production systems, ensuring reliability and rapid issue resolution.
• Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture.
• Lead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies.
• Add to team culture of diversity, opportunity, inclusion, and respect.
• 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

• 8+ years of hands-on practical experience delivering system design, application development, testing, and operational stability using Python, Java, or C++.
• Hands-on experience with AI components, with a strong understanding and opinion of their application in modern technology stacks.
• Foundational understanding of AWS services and best practices, with practical cloud-native experience.
• Proficiency in automation and continuous delivery methods.
• Proficient in all aspects of the Software Development Life Cycle.
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).
• Interest in financial markets and trading, with the ability to work directly with Credit Sales and Trading teams to deliver impactful technology solutions.
• Strong communication skills and a passion for advancing technology through AI and modern engineering practices.

 

Preferred qualifications, capabilities, and skills

• Experience building scalable AI platforms for trading or financial services.
• Experience modernizing legacy systems with AI tooling.