Java​/Python Lead Software Engineer- Trading Systems

Java / Python Lead Software Engineer
- Trading Systems

Columbus, OH, United States

• Job Identification
• Job Category Software Engineering
• Business Unit Asset & Wealth Management
• Posting Date 07/06/2026, 04:24 PM
• Locations 1111 Polaris Pkwy, Columbus, OH, 43240, US
• Job Schedule Full time

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Java / Python Lead Software Engineer
- Trading Systems at JPMorgan

Chase within the Asset Management 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.

We are the industry leader in providing Customized Managed Accounts Solutions(CMAS) where we offer Retail scale investing via our world class investment products developed by JP Morgan Asset Management. Our focus is on mass customization via several innovative avenues offering diverse products and tax smart optionality to our clients. Our business is set to grow given the state of our industry and we are looking to develop a firm lead amongst our peers.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads 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
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Develops distributed systems in Java, React and Python and commits code as a hands on developer
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
• Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language including Java and Python
• Demonstrated hands on experience with Java, Microservices, Springboot, and React
• 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, and in-depth knowledge of the financial services industry and their IT systems
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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…