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 Data Platform & Entitlements at JPMorganChase within the Commercial and Investment Bank, 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 • 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. • 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. • Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development • Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture Required qualifications, capabilities, and skills • Formal training or certification on software engineering concepts and 5+ years applied experience ( • Strong knowledge and practical experience with Java, Spring Framework (Spring Boot, Spring MVC, Spring Data), RESTful APIs, Microservices architectures, and event streaming (Kafka) • 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 • Practical knowledge of CI/CD, Jenkins, and source code management tools such as Git and Bitbucket • Proficiency in designing and implementing data models for relational databases. • Experience working on Cloud platforms for compute and storage needs (AWS/GCP/Azure) • In-depth knowledge of the financial services industry and their IT systems • Practical cloud native experience Preferred qualifications, capabilities, and skills • Experience with modern data platforms / data product engineering such as Databricks– Data Mesh, Unity Catalog, Lake house, Delta, Iceberg • Hands-on experience with Spark and big data processing at scale • Experience with Identity and Access Management platforms, role-based access control, or entitlement governance at scale • Familiarity with authorization models – RBAC, ABAC, ReBAC, Policy and Authorization Engines, Propagation patterns – inheritance hierarchies, group level grants, row/column level security • Exposure to IAM Concepts – SCIM, SSO/OIDC/SAML, service principals and how they map to data-layer permissions. • Experience with LLMs, AI/ML platforms, or enterprise AI integration.