Leads development of secure, scalable, cloud-native front-end software using React and modern JavaScript or TypeScript. Designs microservices-based solutions, writes and reviews production code, troubleshoots technical issues, improves application resiliency, and automates recurring remediation. Drives responsible adoption of AI-assisted engineering tools, evaluates architectural solutions, mentors team members, and collaborates with vendors and stakeholders across the software development lifecycle.
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As a Lead Software Engineer at JPMorganChase within the Commercial and Investment Bank, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
As a Lead Software Engineer at JPMorganChase within the Commercial and Investment Bank, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Deliver end-to-end solutions using cloud-native, microservices-based application
- Identify opportunities to eliminate or automate remediation of recurring issues
- 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.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
Continuously update technologies and patterns. Design and build solutions that avoid single points of failure
Design and build scalable, secure, and reliable solutions using modern architectural patterns
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
Proficiency with modern front-end stacks: JavaScript or Typescript, using React or frameworks
Ability to independently solve design and functionality challenges with minimal supervision
Understanding of modern design patterns used in JavaScript
Knowledge and experience working with HTML5, CSS, and pre-compilers like Sass and LESS
Experience with agile development methodologies and understanding of the software development life cycle
- Solid understanding of UI/UX principles, accessibility, and responsive design.
- 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
- Proficient in all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
- Experience with containerization (Docker, Kubernetes) and cloud platforms (AWS).
- Familiarity with RESTful APIs and microservices architecture.
Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management
Strong problem-solving, analytical, and communication skills
Ability to drive broader impact by sharing and contributing best practices
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