Java Kafka Streaming 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 JPMorganChase within the Consumer & Community Banking Marketing and Customer Insights 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 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 breakdown technical problems Lead design and delivery of Kafka-based event streaming platforms/services in high-throughput (high TPS) environments; deep experience with event-driven architecture patterns and distributed systems reliability Code in back-end technologies (e.g., Java, Springboot, Node.js ) with experience building microservices-based applications Code in front-end technologies (e.g., HTML, CSS, JavaScript, Typescript, React, Angular) Work with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON Develops secure and high-quality production code, and reviews and debugs code written by others 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. 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 Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience Proficiency in back-end technologies (e.g., Java, Springboot, Node.js ) with experience building microservices-based applications for full-stack roles (e.g., HTML, CSS, JavaScript, Typescript, React, Angular) Experience leading design and delivery of Kafka-based event streaming platforms/services in high-throughput (high TPS) environments (deep experience with event-driven architecture patterns and distributed systems reliability) Demonstrated ability to independently solve design and functionality challenges with minimal supervision Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets and JSON Hands-on experience designing and building scalable applications using SQL and NoSQL databases Proven ability to lead technical direction: drive architecture decisions, write/own design docs, align stakeholders, and deliver through ambiguity Experience improving operability (SLOs/SLAs, on-call readiness, monitoring, incident response, postmortems) for streaming systems 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 Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Preferred qualifications, capabilities, and skills Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management Strong problem-solving, analytical, and communication skills Ability to drive broader impact by sharing and contributing best practices AWS certification Experience building and operating high-volume data processing pipelines using Apache Spark (Spark SQL, Structured Streaming) and/or Apache Flink (DataStream/Table API) in production.