Senior Lead Software Engineer - Java Fullstack, AWS, AI - Business Banking

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products. As a Senior Lead Software Engineer at JPMorgan Chase within the Consumer and community banking technology - Business Banking 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications. Job responsibilities Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain. Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale. Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors. Develops secure and high-quality production code, and reviews and debugs code written by others. Drives decisions that influence product design, application functionality, and technical operations and processes. Serves as a function-wide subject matter expert in one or more areas of focus. Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience Demonstrated experience using approved AI-assisted engineering tools and practices across the software development lifecycle, with an understanding of validation, secure coding, peer review, automated testing, and responsible adoption at scale. Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls. Deep expertise in Java 8+ / Spring Boot, microservices, and React/Angular. Strong Kafka/event-driven architecture experience (retries, idempotency, DLQ patterns, schema/versioning). Experience with SQL databases with data modelling, query optimization and performance tuning. Strong NoSQL experience: Cassandra / DynamoDB / Elastic Search (data modeling, reliability, scale). Strong experience with Cloud Foundry/AWS and CI/CD strategy and execution. Ability to work with tools such as Dynatrace, Splunk, Grafana for observability and monitoring Experience building applications with resilient, highly available architectures, including consideration for failure modes, recovery, and operational readiness. Preferred qualifications, capabilities, and skills Working knowledge of secure engineering practices and designing to meet Cyber Security and Technology Control requirements (e.g., authentication/authorization, secure APIs, data protection, dependency hygiene). Demonstrated leadership in design reviews, mentoring, and cross-team technical alignment.