Lead Software Engineer - Full Stack/AI Engineering Focus

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank - Digital & Platform Services 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. 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

• Design, develop, and deliver scalable, secure, and resilient full-stack solutions using Java/Spring Boot, React, and TypeScript, applying strong engineering judgment to meet functional and non-functional requirements while solving complex business and technical challenges.

• Own the end-to-end delivery lifecycle for strategic platform capabilities and application features, including requirements analysis, solution design, development, testing, deployment, production support, and continuous improvement.

• Lead the design and development of cloud-native, containerized microservices and platform services, emphasizing domain-driven design, API-first development, performance optimization, security, maintainability, and operational excellence.

• Drive technical architecture and design decisions across the technology stack, collaborating with product managers, architects, and engineering teams to ensure alignment with enterprise architecture standards and long-term technology strategies.

• Build and enhance high-performance backend services and APIs (REST/GraphQL), integrating with enterprise platforms, relational databases, search technologies, and distributed data systems.

• Develop modern operational and administrative user interfaces using React and TypeScript, delivering intuitive experiences that improve platform usability, productivity, and supportability.

• Design and implement event-driven and streaming architectures leveraging Kafka, including event modeling, schema governance, topic strategy, and resilient producer-consumer patterns to enable scalable and loosely coupled systems.

• Champion engineering excellence through code reviews, troubleshooting, refactoring, performance tuning, and mentoring, while raising quality standards across the team.

• Lead initiatives to improve application reliability, observability, and operational stability through automation, proactive monitoring, distributed tracing, incident management, root cause analysis, and continuous reduction of technical debt.

• Leverage enterprise-approved AI-assisted engineering tools and platforms to accelerate software delivery, improve developer productivity, automate repetitive tasks, and enhance code quality while adhering to established governance, security, and validation practices.