Lead Software Engineer - Java, Spring Boot, Microservices

Be part of the Digital Markets Execution Technology team to lead the development of our Markets Execute platform. You will lead a team of Java and React developers, partner closely with Product, Delivery, and Sales and Trading, and own the long-term technical vision and stability of our platform.

As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank's Digital Markets Execution Technology team, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure and scalable way. You will execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role. You must be a passionate and well-rounded technologist with demonstrated leadership, committed to continuous learning and improvement. You will also establish and track reliability goals, implement robust observability, and lead stability initiatives (resilience patterns, incident response, post-incident reviews)

Job Responsibilities

• Lead and grow a cross-functional engineering team (Java backend and React frontend); drive delivery predictability and quality.
• Partner with Product and Delivery to shape roadmaps, prioritize work, manage dependencies, and de-risk releases.

• 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.

• Own the platform’s long-term technical vision and architectural runway; set guardrails, integration contracts, versioning, and deprecation paths.
• Establish and meet reliability goals; implement observability and resilience patterns.
• Lead incident response and post-incident reviews; reduce MTTR, lower change failure rate, and elevate production readiness.
• Maintain secure-by-default practices (authentication/authorization, secrets management, dependency hygiene) and uphold risk and controls.
• Remain hands-on: architect and implement high-performance Java services; perform profiling/tuning; collaborate with React developers on API design and backward-compatible rollout strategies.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Excellent understanding of Java 17+ fundamentals, concurrency, memory management, and object-oriented programming paradigms.
• Hands-on experience with Spring and server-side frameworks (e.g., Spring Boot) and strong API design skills.
• Experience building high-performance, latency-sensitive Java applications. Experience with microservices deployment topologies on Kubernetes.
• Proven partnership with Product, Delivery/Program, and business stakeholders; converting business requirements into technical roadmaps, OKRs, and measurable deliverables.
• Experience owning the evolution and stability of mission-critical platforms: architectural modernization, operability, performance, and cost-effectiveness.
• Clear understanding of messaging technologies and computer networks; familiarity with FIX and Solace. Experience maintaining and troubleshooting software in Linux environments.

• Demonstrated experience leading effective use of 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, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

   

• Test-driven development using modern source control and continuous integration; strong CI/CD and release governance.
• Experience working with globally distributed engineers; strong communication with technical and non-technical audiences.

Preferred qualifications, capabilities, and skills

• Demonstrated experience leading an engineering team; mentoring, coaching, and fostering an inclusive, high-performing culture.
• Familiarity with Python and React.
• Familiarity with investment banking, fintech, or financial markets.