JPMorgan Chase
Senior Lead Software Engineer (Java/AWS) — Alternatives Technology
575 Washington Blvd, Jersey City, NJ 07310
Full-time
First seen by offpeak October 21, 2026
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As a Senior Lead Software Engineer at JPMorganChase within the Asset & Wealth Management, Alternatives Team, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications. You will be a hands-on Java/Spring Boot tech lead building and modernizing platforms that support alternative investments and the teams that service them. You will help re-platform critical applications from on‑premises to AWS, delivering cloud-native services with strong engineering discipline across system design, development, testing, and operational stability. You will shape distributed integration patterns, including messaging and event streaming, to improve resiliency, scalability, and observability. You will also lead effective use of enterprise-authorized AI-assisted development tools, setting team expectations for validating AI outputs for correctness, performance, and security.
Job responsibilities
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Serves as a function-wide subject matter expert in one or more areas of focus
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Proven hands-on experience delivering system design, application development, testing, and operational stability in production environments
- Advanced proficiency in Java (enterprise backend development), with strong practical experience building services using Spring Boot (or equivalent Java frameworks)
- Hands-on experience designing, building, and operating integrations using messaging and/or event streaming services (e.g., Kafka, AWS MSK, SQS/SNS, Kinesis), including reliable delivery patterns, error handling, and observability in production
- Practical, hands-on cloud-native experience (the team’s target platform is AWS), including building/deploying/operating services in a cloud environment
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
- Ability to tackle design and functionality problems independently with little to no oversight
- Reactive programming experience (e.g., Reactor) and event-driven / messaging & streaming familiarity
- Financial services / wealth or alternatives domain experience