Sr. Lead Software Engineer-Full Stack/Java/AWS

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Sr. Lead Software Engineer-Full Stack/Java/AWS at JPMorgan Chase within the Corporate and Investment Banking Payments Technology 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. 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 Own the technical strategy and architecture for mission-critical applications, aligning solutions with business goals, industry best practices, and roadmap decisions while representing engineering in strategic discussions Leads and mentors a team of software engineers, providing guidance, support, and professional development opportunities Drives the design and implementation of high-performance backend services using Java and cloud-native technologies Sets and enforces standards for API design and development (REST/gRPC), including best practices for versioning, documentation, and error handling to ensure robust, secure, and scalable interfaces Champions highly resilient, share-nothing, multi-region architectures to achieve fault tolerance, high availability, and disaster recovery Guides the integration and management of service registries for dynamic service discovery and orchestration in microservices environments Promotes the creation of custom frameworks and reusable components to accelerate development and maintain consistency Fosters and manages Agile, self-managing team practices and project delivery, driving continuous improvement in processes, tools, and standards while ensuring timelines, quality, stakeholder satisfaction, and proactive mitigation of technical risks 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. Required qualifications, capabilities, and skills Formal training or certification on Software Engineering concepts and 5+ years applied experience Extensive experience in Java and object-oriented programming. Proven technical leadership delivering solutions with Java, React, Spring Boot, Kafka, and Oracle Database. Strong experience building cloud-native applications and leading Kubernetes-based engineering efforts. Hands-on expertise with cloud platforms (AWS, Azure, GCP), including practical cloud-native design and implementation. Strong background in RESTful and gRPC API design, development, and implementation. Demonstrated experience with API best practices and service registry concepts in distributed systems. Demonstrated proficiency across modern software engineering disciplines and technical processes (e.g., cloud, artificial intelligence, machine learning, mobile, etc.). In-depth financial services domain knowledge, including experience in Banking and/or Payments environments and related IT systems, with a track record of designing highly resilient, share-nothing, multi-region architectures and applying advanced agile/DevOps practices (e.g., CI/CD, automation/continuous delivery, application resiliency, security). 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. Preferred qualifications, capabilities, and skills Proven experience in senior leadership or engineering management roles UI development experience with modern frameworks such as React, Angular, or similar Experience within a Banking and/or Payments environment Experience working with Cloud Foundry, Jenkins, and/or Docker.