Director of Software Engineering - Machine Learning/AI

If you are a software engineering leader ready to take the reins and drive impact, we’ve got an opportunity just for you. As a Director of Software Engineering at JPMorganChase within Wholesale Credit Risk Technology, you lead a technical area and drive impact within teams, technologies, and projects across departments. Utilize your in-depth knowledge of software, applications, technical processes, and product management to drive multiple complex projects and initiatives, while serving as a primary decision maker for your teams and be a driver of innovation and solution delivery. Job responsibilities Leads technology and process implementations to achieve functional technology objectives Accountable for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures Sets direction and governance for agentic AI-enabled engineering and SDLC/TLM automation within a technical area to drive measurable improvements in speed, quality, and operational outcomes (e.g., AI-orchestrated delivery workflows, release readiness controls, automated test modernization, and incident triage acceleration), while establishing guardrails for validation, security, resiliency, traceability, and reuse across teams. 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 and support capacity unlock initiatives at scale. Carries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations Delivers technical solutions that can be leveraged across multiple businesses and domains Influences peer leaders and senior stakeholders across the business, product, and technology teams Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and advanced applied experience Experience developing or leading cross-functional teams of technologists Experience with hiring, developing, and recognizing talent Experience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorized tools within the work environment) across teams, including defining operating expectations (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs. Strong understanding of responsible AI use and control expectations in engineering workflows, including data sensitivity, resiliency/security implications, and governance; ability to influence leaders on safe scaling patterns and reuse. Practical cloud native experience Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field Preferred qualifications, capabilities, and skills Worked on agentic platforms