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Java Lead Software Engineer — Digital Markets Execution Technology, Execute

JPMorgan· LONDON, LONDON, United KingdomLicensed sponsor
Posted 29 Jun 2026 · Added 29 Jun 2026, 09:40
JPMorgan3.9 (20,400)10,000+ employees

Headquartered in New York City, JPMorgan Chase is the largest bank in the United States.

Levels.fyi · global compSWE $164k TC ($122k–$205k)
AI summary

Java 17+, Spring/Spring Boot, microservices, Kubernetes, Linux, messaging (MQ/Kafka, FIX, Solace), and CI/CD tooling. The team builds and delivers high-performance, latency-sensitive trading systems and platform services for JPMorgan’s Digital Markets Execution Technology.

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As a Lead Software Engineer at JPMorganChase within Digital Markets Execution Technology, Execute, 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 and oversees end-to-end software solutions, engineering standards, architecture, and technical troubleshooting for trading systems

Designs and builds high-performance, latency-sensitive services with awareness of upstream/downstream system dependencies

Develops secure and high-quality production code, and reviews and debugs code written by others

Leads technical analysis, estimation, planning, code reviews, architecture sessions, and retrospectives to drive delivery outcomes

Establishes reliability goals and implements observability, resilience patterns, and operational readiness practices

Leads incident response and post-incident reviews to improve production stability and performance; identifies recurring issues and drives automation/remediation

Upholds secure-by-default engineering practices and risk/control standards across the SDLC

Guides integration contracts, API/versioning strategies, and deprecation paths for platform services

Drives team adoption of enterprise-authorized AI-assisted engineering practices across the SDLC toolchain to improve code quality, delivery speed, and operational outcomes, while setting validation standards for correctness, performance, and security

Mentors engineers and contributes to a culture of inclusion, respectful collaboration, and continuous improvement aligned to measurable outcomes

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and advanced applied experience (EMEA/LATAM-Brazil)

Hands-on practical experience delivering system design, application development, testing, and operational stability for mission-critical platforms

Advanced in one or more programming language(s), with deep hands-on expertise in Java (17+), including concurrency, memory management, and object-oriented design

Demonstrated experience designing clean APIs and rollout strategies for distributed systems (including integration and backward compatibility considerations)

Practical experience with Spring/Spring Boot, microservices, Kubernetes, Linux, and core networking/messaging concepts

Proficient in all aspects of the Software Development Life Cycle, including CI/CD, automated testing practices, application resiliency, and security

Demonstrated experience leading effective use of enterprise-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 and secure handling of inputs/outputs, aligned to resiliency and security expectations

Effective communication with technical and non-technical audiences; ability to operate in globally distributed teams

Preferred qualifications, capabilities, and skills

Exposure to messaging systems and market protocols (e.g., MQ/Kafka; familiarity with FIX and Solace)

Experience with observability stacks and resilience engineering for low-latency / latency-sensitive platforms

Familiarity with Python

Experience operating services in regulated environments with strong auditability and controls