Lead Java Engineer for Low-Latency Liquidity Trading

JPMorgan Chase & Co.; Columbus (OH); On-site; USD 130,000 - 180,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Lead Software Engineer (Java) to advance liquidity trading capabilities within Morgan Money for Asset & Wealth Management.

You will be a hands-on engineer delivering secure, high-performance Java services while partnering with trading stakeholders to drive measurable business outcomes. The role requires building resilient distributed systems, ensuring operational readiness, and driving continuous improvement in engineering practices, observability, and

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Hands-on experience delivering production-grade backend services using Java with strong object-oriented design and debugging skills.
• Experience building scalable distributed systems with a focus on low-latency performance, resiliency patterns, and failure-mode thinking.
• Proficiency with modern Java frameworks (e.g., Spring) and dependency injection patterns to build maintainable services.
• Demonstrated experience implementing strong testing practices (unit, integration, and contract testing) and using automated quality gates.
• Experience with messaging and streaming technologies (Kafka or enterprise messaging platforms) and event-driven design patterns.
• Strong understanding of secure coding practices and the ability to design and implement controls that reduce operational and technology risk.
• Demonstrated experience leading effective use of approved AI-assisted software development tools 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.

Responsibilities

• Partner with investment and trading teams to translate business objectives into durable, measurable technical outcomes
• Design, build, and operate low-latency backend services in Java with a focus on scalability, resiliency, and secure-by-design engineering
• Own end-to-end delivery of features from design through production release, ensuring operational readiness and strong customer outcomes
• Drive architecture and engineering decisions that improve performance, reliability, and long-term maintainability across services
• Establish and uphold disciplined engineering practices, including automated testing, code review, and continuous integration and delivery
• Improve observability and incident readiness through effective logging, metrics, tracing, and production diagnostics to reduce time to detect and recover
• Drives team adoption of enterprise-authored AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes, while establishing consistent validation standards and promoting reuse of patterns
• Applies knowledge of tools within the SDLC toolchain, including enterprise-authored AI-assisted development and automation capabilities, to improve the value realized by automation

Skills

Java

Spring Framework

Distributed Systems

Low Latency

Testing Practices

AI-assisted tooling

Secure Coding

Code Review

Mentoring/Leadership

Education

Software engineering certification

Tools

Kafka

CI/CD

Observability platforms

Job description

JPMorgan Chase & Co. is seeking a Lead Software Engineer (Java) to advance liquidity trading capabilities within Morgan Money for Asset & Wealth Management.

You will be a hands-on engineer delivering secure, high-performance Java services while partnering with trading stakeholders to drive measurable business outcomes. The role requires building resilient distributed systems, ensuring operational readiness, and driving continuous improvement in engineering practices, observability, and