Lead Software Engineer - API Platform

Lead Software Engineer 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 & Community Banking - API Marketplace 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. You will play a pivotal role in designing, building, and enhancing the API Platform that empowers our API developers. We seek engineers with a broad technical perspective and a passion for solving complex challenges using expertise across multiple disciplines. In this role, you will manage end-to-end problem-solving, advocate for effective solutions across diverse technology stacks, and help drive significant business value for our customers through robust API offerings. Job Responsibilities Brings discipline and creativity to solve business-critical problems, working with tech leads, product managers, and designers to bring outcomes to fruition Identifies opportunities to remove technical debt and works to improve the quality of engineering deliverables Communicates with stakeholders and is comfortable leading discussions with customers Develops secure and high-quality production code, and reviews and debugs code written by others Drives decisions that influence product design, application functionality, technical operations, and processes, providing leadership grounded in technical expertise and effective communication Serves as a function-wide subject matter expert in one or more areas of focus Contributes to the engineering community as an advocate for firmwide frameworks, tools, and practices of the Software Development Life Cycle 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 5+ years applied experience. Hands-on practical experience delivering system design, application development, testing, and operational stability Hands-on programming/application development experience utilizing Java, Spring Boot, REST, Microservices, RDBMS and NoSQL databases, Cloud Native, Agile, DevOps, and TDD Recent experience with a cloud platform such as AWS, and utilization of container technologies such as Docker and Kubernetes Prior experience in building or using API Platforms, with deep expertise in one or more areas of the end-to-end API stack, including cloud connectivity, network diagnosis, resilient systems, API security, authentication/authorization, API gateways, and API design spanning specification, standards, documentation, and governance. Advanced knowledge of software applications and technical processes, with considerable in-depth expertise in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Ability to tackle design and functionality problems independently with little to no oversight Practical cloud native experience Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field 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 Deep understanding of networking and connectivity, including diagnosing network latencies, DNS behavior, cloud connectivity, and content delivery networks Strong knowledge of API security, including transport-level security, payload encryption, signature algorithms, certificate management, OAuth, and DDoS protection Experience designing highly scalable and resilient software systems on public cloud platforms such as AWS, utilizing various resiliency design principles and practices Expertise in API developer specifications, standards, and documentation, with prior experience driving adoption of best practices at scale Knowledge or familiarity with modern front-end technologies is a plus Knowledge or experience with data engineering, data pipelines, or analytics platform is a plus Chase