We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As part of JPMorganChase's Corporate Technology organization, you will work alongside talented engineers, designers, and product leaders on meaningful, high-impact problems — all while growing your craft in one of the world's most dynamic technology organizations. Here, your contributions matter, your ideas are heard, and your growth is supported at every stage.
As a Lead Software Engineer at JPMorganChase within Corporate Technology, you will play a central role in designing and delivering high-quality, scalable software solutions that power critical business capabilities across the firm. You will bring deep full-stack expertise — spanning Java, Angular, and modern microservices architecture — and apply it to drive engineering excellence, mentor your peers, and align delivery to product and business priorities. Your work will directly influence how technology is built, shared, and sustained across distributed teams, and your leadership will help shape the engineering culture of the teams you work with.
Job responsibilities
- Design and deliver scalable, high-quality full-stack solutions using Java and Angular, applying strong engineering principles and attention to UI quality and detail
- Define and enforce engineering standards, reusable templates, and shared components to improve consistency, reduce duplication, and accelerate delivery across teams
- Architect and implement microservices-based solutions, applying sound design patterns and principles appropriate for enterprise-scale environments
- Partner with UX designers and product owners to rapidly prototype solutions, incorporate iterative feedback, and align delivery to the product roadmap
- Drive adoption of modern software development lifecycle practices, including continuous integration and delivery, clear versioning strategies, and automated testing
- Mentor and coach engineers across the team, fostering a culture of technical excellence, ownership, and continuous improvement
- Influence architecture decisions and contribute to cross-functional technical discussions, bringing clarity and direction to complex engineering challenges
- Manage competing priorities and changing requirements in a fast-paced environment, delivering predictable outcomes with minimal direction
- Communicate delivery progress, risks, and technical decisions clearly to stakeholders including business analysts, product managers, and technology partners
- 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
- Expert-level proficiency in HTML, CSS, and JavaScript, with demonstrated attention to UI quality and detail
- Strong hands-on development experience with Java (version 8 or higher) in enterprise environments
- Strong hands-on development experience with Angular (version 6 or higher), including component-based architecture and state management
- Deep understanding of microservices patterns and design principles, with practical application in large-scale production systems
- Proven ability to set engineering standards and define reusable templates and components that improve delivery efficiency and consistency
- Demonstrated experience mentoring engineers and collaborating effectively with distributed, cross-functional teams
- Working knowledge of modern software development lifecycle toolsets and practices, including continuous integration and delivery pipelines and branching strategies
- Strong problem-solving skills with the ability to drive issues to resolution with appropriate urgency and rigor
- 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 strengthening operational practices through structured problem solving, root-cause analysis, and preventative improvements in production environments
- Experience driving consistency through shared engineering practices, templates, and reusable building blocks across teams
- Agile experience, including iterative planning, delivery, and continuous improvement practices
- Familiarity with enterprise-scale delivery across geographically distributed teams and complex stakeholder environmentss
