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Lead Software Engineer (UI) — Digital Markets Execution Technology (DMET), Execute
lead · Technology / Software Development
Are you ready to shape the future of front-office technology at one of the world's most influential financial institutions? At JPMorganChase, we build platforms that move markets — and we're looking for engineers who want to lead at the intersection of performance, design, and scale. Here, your work will be seen, felt, and used by traders and sales professionals every day.
As a Lead Software Engineer (UI) at JPMorganChase within Digital Markets Execution Technology, you will set the front-end technical direction for Execute — our front-office trading platform powering Markets businesses globally. You will lead hands-on delivery of latency-sensitive, real-time user experiences used directly by traders and sales, partnering closely with product specialists, designers, business stakeholders, and control partners. This role is for an engineer who thrives on technical ownership, engineering excellence, and building intuitive, high-signal workflows at scale in a fast-paced global environment.
Job responsibilities
- Lead the design and delivery of user interface capabilities across Execute, from discovery through to production support
- Set front-end technical direction, including architecture, standards, performance benchmarks, and testing strategy
- Partner with product, business stakeholders, and designers to translate complex trading workflows into intuitive, high-performance user experiences
- Build real-time, data-intensive UIs with strong responsiveness, stability, and low-latency characteristics suited to front-office trading environments
- Establish and evolve scalable UI architecture, including component libraries and shared platform services
- Drive engineering excellence through code reviews, quality gates, CI/CD pipelines, observability practices, and operational readiness
- Ensure secure, compliant development practices aligned to firm standards and control expectations
- Mentor and develop engineers, cultivating an inclusive, high-performing team culture
- Collaborate with backend, platform, and site reliability partners to deliver end-to-end solutions
- 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 advanced applied experience
- Hands-on experience building production user interfaces with React and TypeScript in large-scale applications
- Strong knowledge of modern front-end engineering, including state management, asynchronous data flows, and UI architecture patterns
- Expertise in performance optimization, testing strategies, and automation within CI/CD pipelines
- Experience delivering real-time or data-intensive user experiences in complex, high-availability environments
- Demonstrated technical leadership in setting standards, leading design reviews, and mentoring engineering teams
- Solid software engineering fundamentals, including object-oriented design patterns, debugging, and technical documentation
- Strong communication skills with the ability to work effectively across global, cross-functional teams
- 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 in front-office trading, electronic execution, or capital markets technology domains
- Familiarity with financial market concepts, trading protocols, and execution workflows
- Experience with advanced data grid patterns, UI component libraries, and data visualization at scale
- Exposure to backend-for-frontend patterns, event-driven architectures, and API design collaboration
- Experience operating user interfaces in regulated environments with strong auditability and controls requirements
- Full-stack proficiency, including back-end technologies such as Java or Spring Boot, and experience building microservices-based applications