Director of Software Engineering and AI - Operations
Salary not listed • Plano, TX, United States • Full-time
Posted 1mo ago
No salary is listed. Many US states require employers to post a pay range, so ask about pay early.
Job Location
Plano, TX, United States
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Engineer
About the job
As a Director of Software Engineering at JPMorgan Chase within Operations Collections, you will lead a technical area and drive impact across teams, technologies, and projects. You will utilize your in-depth knowledge of software, applications, technical processes, and product management to drive multiple complex projects and initiatives. You will serve as a primary decision-maker for your teams and be a driver of innovation and solution delivery.
Responsibilities
- Lead technology and process implementations to achieve functional technology objectives.
- Be accountable for decisions influencing teams' resources, budget, tactical operations, and process execution.
- Set direction and governance for agentic AI-enabled engineering and SDLC/TLM automation to improve speed, quality, and operational outcomes.
- Apply knowledge of Software Development Life Cycle tools, including AI-assisted development, to improve automation value and unlock capacity.
- Carry governance accountability for coding decisions, control obligations, and measures of success like cost of ownership and maintainability.
- Deliver technical solutions that can be leveraged across multiple businesses and domains.
- Influence peer leaders and senior stakeholders across business, product, and technology teams.
Requirements
- 10+ years of applied software engineering experience with formal training or certification.
- 5+ years of experience leading technologists to manage and solve complex technical challenges.
- 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 across teams, including defining expectations, measuring outcomes, and ensuring secure handling of sensitive data.
- Strong understanding of responsible AI use and control expectations in engineering workflows.
- Practical cloud-native experience.
- Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field.