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