Lead Software Engineer - React

JPMorganChase•Chicago, IL

About The Position

As a Lead Software Engineer at JPMorgan Chase within Corporate Technology, you will be an integral member of an agile team enhancing, building, and delivering trusted technology products in a secure, stable, and scalable way. You will apply deep technical expertise and problem-solving skills to challenges across technologies and applications, driving business impact through your work. The role involves leading software design and development, making architectural decisions for distributed systems, and developing secure, high-quality production code. You will collaborate with UX designers and product owners to translate requirements into intuitive interfaces, work with backend teams on scalable APIs, and help improve operational stability through automation. You will also promote effective and responsible use of enterprise-authorized AI-assisted engineering tools, establishing validation practices and coaching team members on secure, compliant adoption.

Requirements

Formal degree or certification in software engineering concepts and at least 5 years of applied experience developing user interfaces, including hands-on React development.
Practical experience delivering system design, application development, testing, and operational stability.
Advanced understanding of agile methodologies, including CI/CD, application resiliency, security, and the Software Development Lifecycle.
Demonstrated proficiency in software applications and technical processes within a technical discipline such as cloud, artificial intelligence, machine learning, or mobile.
In-depth knowledge of the financial services industry and its IT systems.
Practical cloud-native experience.
Commercial experience developing, debugging, and performing automated testing, such as with React Testing Library or Cypress.
Demonstrated experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, or troubleshooting, including setting expectations for validating outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations.

Nice To Haves

Exposure to frontend libraries such as ag-grid, Highcharts, and Redux, as well as TypeScript.
Exposure to performance tuning complex UIs.
Experience working within an Investment Bank or Finance Technology team.
Team management experience.
Experience with a DevOps model, Kubernetes, and cloud auto-scalable infrastructure.

Responsibilities

Execute creative software solutions, including design, development, and technical troubleshooting, and devise approaches to complex technical problems.
Drive architectural decisions for distributed systems, including event-driven pipelines, CQRS patterns, and real-time data streaming.
Develop secure, high-quality production code; review and debug code written by others.
Identify opportunities to eliminate or automate recurring issue remediation to improve application and system operational stability.
Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs, technical credentials, and applicability to existing systems and information architecture.
Lead Software Engineering communities of practice to promote awareness and adoption of new and leading-edge technologies.
Collaborate with UX designers and product owners to translate requirements into intuitive UI screens and user flows.
Contribute to a team culture of diversity, opportunity, inclusion, and respect.
Drive adoption of enterprise-authorized AI-assisted engineering practices, establish consistent validation standards, and promote reuse of effective patterns across the team.
Apply knowledge of Software Development Life Cycle tools, including authorized AI-assisted development and automation capabilities, to improve the value of automation.
Collaborate with backend technology teams to design scalable and reusable RESTful APIs.
Coach engineers on safe and compliant adoption of AI-assisted tools in delivery practices.