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 JPMorgan Chase within the Consumer and community banking technology 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 an emerging senior member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role. You will build AI-native solutions —embedding AI coding tools, agentic workflows, and LLM capabilities into every layer of the platform. We are seeking an experienced Java Distributed Systems Engineer to design, build, cloud-native backend systems. 

Job responsibilities

• Own end-to-end delivery of complex backend components, embedding AI-native capabilities (agentic workflows, LLM-powered features) into core product experiences.
• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• 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.
• Participate actively in design reviews and architecture discussions
• Identify performance bottlenecks and propose optimizations
• Mentor junior engineers through code reviews and technical guidance

• 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 5+ years applied experience.
• Experience in designing and developing distributed systems using Java
• Strong knowledge in Core Java (Java 21+), Spring Boot, React, REST, Kafka, Microservices, Agile, DevOps
• Hands-on practical experience using AI coding assistants (GitHub Copilot, Cursor, Claude, etc.).
• Experience in object oriented analysis and design (OOAD)
• Experience working with cloud platforms such as AWS
• Experience on asynchronous communication using messaging/streaming systems (Kafka, RabbitMQ, or equivalents)
• Ability to design and optimize data models either in relational or NoSQL databases
• Ability to handle data consistency, replication, sharing, and transactional boundaries
• 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

Preferred qualifications, capabilities, and skills
 

• Advanced knowledge of application, data, and infrastructure architecture disciplines
• Strong written and oral communication and excellent presentation and influencing skills
• Familiarity with modern front-end technologies
• Practical cloud native experience
• Knowledge on integration with CI/CD pipelines for automated build, test, and deployment
• Familiar with containerization and orchestration tools: Docker, Kubernetes