Lead an agile engineering team building secure, scalable AI & ML data platform products. Provide technical direction, write and review production-quality code, drive architecture and operational best practices, champion enterprise AI-assisted development and responsible AI use, and promote reuse and engineering standards across the organization.
At JPMorganChase, we build technology that powers one of the world's most important financial institutions — and we want you to be part of it. You'll have the opportunity to lead complex engineering challenges, grow your expertise, and collaborate with talented teams across the globe. We invest in our people, providing the tools, resources, and environment to help you thrive and advance your career. If you're passionate about delivering technology that makes a real difference, this is the role for you.
As a Lead Software Engineer at JPMorganChase within the AI & ML Data Platforms team, 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. You will drive significant business impact through your capabilities and contributions, applying deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications. Your leadership will help shape the direction of our engineering community and the future of our technology.
Job responsibilities
- Provide technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Develop secure and high-quality production code, and review and debug code written by others
- Drive decisions that influence product design, application functionality, and technical operations and processes
- Serve as a subject matter expert in one or more areas of focus, sharing knowledge and best practices across the engineering community
- Actively contribute to the engineering community as an advocate of firmwide frameworks, tools, and practices across the Software Development Life Cycle
- Influence peers and project decision-makers to consider the use and application of leading-edge technologies
- Foster a team culture of diversity, opportunity, inclusion, and respect
- 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 practical experience delivering system design, application development, testing, and operational stability
- Advanced proficiency in one or more programming languages with a strong focus on code quality and maintainability
- Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile)
- Ability to tackle design and functionality problems independently with little to no oversight
- Practical cloud native experience with a strong understanding of scalability, resiliency, and security principles
- Background in Computer Science, Computer Engineering, Mathematics, or a related technical field
- 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 designing and developing modern, responsive front-end interfaces using React, TypeScript, and component-based architecture
- Proficiency in back-end development using Java frameworks (e.g., Spring Boot) for building RESTful APIs and microservices
- Hands-on experience with cloud platforms (e.g., AWS) including container orchestration, serverless computing, and infrastructure-as-code
- Experience with database technologies including relational and NoSQL solutions, caching strategies, and asynchronous messaging patterns
- Strong knowledge of continuous integration and delivery pipelines and automated testing frameworks across front-end and back-end systems
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
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