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# Lead Software Engineering - Trading Tech

- **Company:** JPMorgan Chase & Co.
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Algorithmic Trading, Amazon Web Services, Apache HTTP Server, Behavior-Driven Development, Software Quality, Code Review, Distributed Systems, Financial Information EXchange, IBM WebSphere MQ, Enterprise Messaging Systems, Systems Development Life Cycle, Redis, Software Engineering, Data Streaming, Performance Testing, Test-Driven Development (TDD), Event Driven Architecture, Containerization, Kubernetes, Information Technology, Production Code, Gemfire, Apache Kafka, Non-relational Database, Microservices
- **Published:** October 7, 2026
- **Apply:** https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions/preview/210797429

## About the Role

* Bachelor's degree in Computer Science or a related field, or equivalent practical experience.
 * Hands-on proficiency in Java and a track record of delivering production-quality code.
 * Experience building distributed systems that process high volumes of data with real-time delivery needs.
 * Practical experience with continuous integration and continuous delivery (CI/CD) pipelines and modern delivery practices.
 * Working knowledge of microservices and service-oriented design.
 * Working knowledge of event-driven architectures and messaging patterns.
 * Experience with streaming and/or messaging technologies (for example, Kafka or IBM MQ).
 * Experience with caching technologies (for example, Redis, GemFire, or Apache Ignite).
 * Working knowledge of relational and non-relational databases.
 * Experience working in agile teams with strong engineering hygiene (testing, reviews, and operational readiness).
 * Self-starter mindset with the ability to manage multiple competing priorities and deliver with ownership.

Preferred qualifications, capabilities, and skills

It's a plus if you have:

 * Experience with the Spring ecosystem.
 * Experience building and operating workloads on Amazon Web Services (AWS).
 * Familiarity with trading systems and market structure concepts.
 * Trading floor experience and/or quantitative/trading domain background.
 * Exposure to the Financial Information eXchange (FIX) protocol.
 * Demonstrated ability to troubleshoot mission-critical production issues in distributed environments.
 * A continuous learning mindset and interest in emerging engineering tools and practices.

## Description

As a Vice President, Lead Software Engineering at JPMorgan Chase within Trading Technology, you will help design, build, and run services that support a multi-asset trading platform on Amazon Web Services (AWS). You'll work closely with engineers and partners to turn business needs into resilient, observable, secure software using modern Java and microservices patterns. You'll contribute to technical direction through design discussions, strong engineering practices, and a focus on quality and maintainability. We value curiosity, teamwork, and continuous learning as we evolve a mission-critical platform. We also value clear communication and strong stakeholder engagement as part of day-to-day delivery., In this role, you will:

 * Design, build, test, and deploy services aligned to business and functional requirements.
 * Develop Java-based services using reactive, non-blocking, and streaming patterns where appropriate.
 * Implement microservices and event-driven integrations for real-time distribution workloads.
 * Partner with peers to evolve domain-driven design practices and service boundaries.
 * Use container platforms such as Kubernetes to run scalable services.
 * Apply caching patterns using technologies such as Redis to improve performance and resilience.
 * Participate in code reviews and promote test-driven development and behavior-driven development practices.
 * Support performance testing and resilience validation using appropriate testing and mock frameworks.
 * Work closely with senior stakeholders and cross-functional partners, communicating progress, trade-offs, and risks clearly.
 * Leverage AI-assisted SDLC tooling (agentic development lifecycle) to accelerate delivery while maintaining engineering controls, code quality, and security standards.