Out of the successful launch of Chase in 2021, we’re a new team, with a new mission. We’re creating products that solve real world problems and put customers at the center - all in an environment that nurtures skills and helps you realize your potential. Our team is key to our success. We’re people-first. We value collaboration, curiosity and commitment.

As a Lead Software Engineer at JPMorgan Chase within the accelerator, you are the heart of this venture, focused on getting smart ideas into the hands of our customers. You have a curious mindset, thrive in collaborative squads, and are passionate about new technology. By your nature, you are also solution-oriented, commercially savvy and have a head for fintech. You thrive in working in tribes and squads that focus on specific products and projects – and depending on your strengths and interests, you'll have the opportunity to move between them.

While we’re looking for professional skills, culture is just as important to us. We understand that everyone's unique – and that diversity of thought, experience and background is what makes a good team, great. By bringing people with different points of view together, we can represent everyone and truly reflect the communities we serve. This way, there's scope for you to make a huge difference – on us as a company, and on our clients and business partners around the world.

Job responsibilities

• Significant contributions to designing and building scalable and performant front-end solutions written in TypeScript using React
• Working across B2C and B2B features
• Advocate for and encourage high standards and best practices to maintain high code quality.
  Providing constructive and insightful feedback to teammates, participating in a strong engineering culture.
• Writing testable code, built for scalability, reliability and resilience.
• Working as part of a cross-functional squad, taking ownership of issues and bringing together necessary stakeholders to drive decision making and action.
• An active participant in technical discussions, contributing with insightful and informed opinions to the decision making process.
• 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 proficient advanced experience
• Technical: Highly competent at React with TypeScript, with a strong engineering-first mindset, an ability to solve complex problems elegantly with an emphasis on scalability and performance.
• Adaptability: Thrive in an environment of uncertainty and rapid changes in direction.
  Collaborative Experience: A team player who thrives in working in cross-functional teams, driving things forward.
• Quick Learner: Demonstrate a knack for rapid learning and possess an ambitious, results-driven personality.
• Strong Communication: Excellent communication and organizational skills to work effectively within a fast-paced, high-performing team.
• Team Player: Ability to excel as part of a cohesive team in a high-speed environment.
• As our company continues to expand, you can expect new and exciting growth opportunities to arise swiftly.
• 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