JPMorgan Chase—Lead Software Engineer - Java Fullstack, AWS

Job description

Description: Be an integral part of an agile team that continually pushes the envelope to enhance, build, and deliver high-quality technology products. As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Banking and Reconciliation team, you will play a critical role in designing, building, and delivering secure, stable, and scalable solutions. You will bring deep expertise in Java full-stack engineering, system design, and software architecture, and you will be expected to drive end-to-end deliveries—from requirements and architecture through build, test, release, and production support. Job Responsibilities - Lead end-to-end delivery of complex initiatives: translate business outcomes into technical designs, plan execution, drive delivery milestones, and ensure production readiness. - Provide technical guidance and direction to business and technical teams, including contractors and vendors. - Build secure, high-quality production code (Java full stack) and conduct thorough code reviews; debug and uplift code written by others. - Own system design and architecture decisions: define service boundaries, APIs/contracts, data models, resiliency patterns, scalability strategies, and non-functional requirements (performance, security, availability). - Drive decisions that influence product design, application functionality, and technical operations/processes (CI/CD, observability, incident response, reliability). - Serve as a function-wide subject matter expert in one or more focus areas (e.g., Java microservices, cloud-native architecture, distributed systems, AWS). - Actively contribute to the engineering community as an advocate of firmwide frameworks, tools, and SDLC best practices. - Influence peers and project decision-makers to adopt leading-edge technologies and modern engineering patterns. - 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. Required Qualifications, Capabilities, and Skills - Formal training or certification on software engineering concepts and 5+ years applied experience - Advanced hands-on experience in Java with strong grasp of backend engineering fundamentals (concurrency, performance, security, testing). - Proven ability to deliver system design, application development, testing, and operational stability in production environments. - Demonstrated strength in design and architecture: microservices and distributed systems patterns, event-driven architecture, API design, data consistency, resiliency and fault tolerance. - Ability to tackle design and functionality problems independently with little to no oversight; comfortable acting as the engineering “driver” to unblock delivery. - Practical cloud-native experience, including building, deploying, and operating services on cloud platforms. - Strong ownership mindset with the ability to drive quality across the SDLC: design reviews, implementation, automation, release, and ongoing support. - 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 Preferred Qualifications, Capabilities, and Skills - Experience in AWS (e.g., designing/deploying cloud-native services, security and IAM concepts, monitoring/observability, cost-aware design).