Lead Fullstack Software Engineer - Java, React, AWS

Join JPMorganChase, where your engineering expertise powers decisions that matter on a global scale. As part of Markets Technology, you'll work alongside some of the brightest minds in the industry, building resilient, high-impact systems that support critical functions across the firm. We offer an environment where innovation is encouraged, growth is supported, and your contributions directly influence the product and business. As a Lead Full-stack Software Engineer at JPMorgan Chase within the Corporate & Investment Bank (CIB) Research Technology team, you will play a pivotal role in promoting engineering excellence across the Research Platform. A large transformation of our client-facing platform is underway, and this role offers the opportunity to help shape its direction. You will leverage your full-stack expertise in a collaborative, high-performing environment to design, build, and enhance scalable, resilient solutions that support a rapidly evolving business. In this role, you will lead end-to-end engineering efforts that power the core capabilities of our platform, ensuring robust performance, reliability, and continuous improvement. Job responsibilities Lead and own end-to-end frontend deliverables across the Research Platform — from discovery through to architecture, delivery, and production Architect frontend solutions in a platform-first approach, balancing the needs of our external clients, internal stakeholders, and partner teams Collaborate with product managers and cross-functional engineering teams to translate complex business requirements into technical solutions Advance our ability to deliver frontend strategically — shaping SDLC practices, delivery mechanisms, and UI frameworks that scale across the platform Mentor and guide engineers, fostering a culture of technical excellence, continuous learning, and innovation Uphold a disciplined engineering standard — strong engineering practices, testing, accessibility, and compliance awareness — ensuring quality is built in by default Contribute to the evolution of the team's technology strategy, evaluating emerging tools and frameworks to bring value to the technology stack 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 Proven end-to-end autonomous ownership of complex frontend deliverables involving multiple teams and stakeholders Deep, current expertise in a modern Full- Stack technologies including Java, React, Vue, Svelte, Angular, or equivalent)— comfortable across the stack and with modular or microserices architectures Experience working with a design system (Material, Fluent, Carbon, Radix, Bootstrap, or equivalent), partnering closely with UX and product design Strong testing discipline (unit, integration, end-to-end) and familiarity with modern frontend build tooling (Vite, Turbopack, Webpack) Experience designing and deploying scalable, resilient cloud-native applications on AWS, Azure, or Google Cloud Strong problem-solving skills with the ability to manage and resolve complex technical challenges independently Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices Preferred qualifications, capabilities, and skills Experience working within Financial Services or regulated technology environments Experience partnering with design teams, translating style guides, and implementing modern web standards Experience of engineering delivery using modern frontend SDLC frameworks, leveraging agentic practices Ability to manage the risk and controls agenda across a technology portfolio