Lead Software Engineer - Java, AI and Kafka

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 - Payment Platform 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 Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Lead and inspire a team of entry-level to mid-level software engineers, fostering a culture of collaboration, innovation, and excellence Oversee technical design, architecture, and implementation to ensure high-quality, scalable solutions Produce architecture and design artifacts for complex applications, ensuring that design constraints are met during software code development Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets to support continuous improvement of software applications and systems 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 Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies 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 8+ years applied experience 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 Hands-on practical experience delivering system design, application development, testing, and operational stability Proficient in all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Ability to tackle design and functionality problems independently with little to no oversight Proficiency in Java, REST, and microservices, with experience building event-driven microservices and Kafka streaming Experience with Spring Framework, Spring Boot, and public or private cloud infrastructure Proven record of providing end-user support with excellent problem-solving abilities Preferred qualifications, capabilities, and skills Exposure to AI - using python, AI, Copilot in VScode/Intellij knowledge of Containerization and Container Runtime/Orchestration platforms (Docker/Kubernetes/ECS etc) knowledge about messaging – Kafka knowledge about Relational/NoSQL databases