Lead Full Stack Software Engineer - Multiple Teams

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