Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
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
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 in Java / Python
- 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