Senior Lead Software Engineer Java and architect

If you are looking for a game-changing career, working for one of the world's leading financial institutions, you’ve come to the right place. As a Senior Vice President Software Engineer at JPMorganChase within the Digital Technology team, you provide expertise and engineering excellence as an integral part of an agile team to enhance, build, and deliver trusted market-leading AI-enabled products in a secure, stable, and scalable way. Leverage your advanced technical capabilities and collaborate with colleagues across the organization to drive best-in-class outcomes across various technologies to support one or more of the firm’s portfolios. Job responsibilities Creates complex and scalable coding frameworks using appropriate software design frameworks Develops secure and high-quality production code, and reviews and debugs code written by others Architects and governs agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams Advises cross-functional teams on technological matters within your domain of expertise Serves as the function’s go-to subject matter expert.Contributes to the development of technical methods in specialized fields in line with the latest product development methodologies 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. Creates durable, reusable software frameworks that are leveraged across teams and functions Influences leaders and senior stakeholders across business, product, and technology teams Help define enterprise-scale, target state, AI-enabled architecture for solutions in the Consumer & Community Banking division, to define best-in-class and next generation customer experiences Collaborate with product and engineering to define roadmaps and solution architectures towards target state Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 10+ years applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability Expert in one or more programming language(s) Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse Experience applying expertise and new methods to determine solutions for complex technology problems in one or more technical disciplines Understanding of the business and practical cloud native experience Preferred qualifications, capabilities, and skills Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field Advanced knowledge of software architecture, applications, and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)