lead responsible AI adoption, utilize AI in their own workflows, and contribute to the design of AI-enabled products and processes.  The ideal candidate brings a strong blend of instructional design expertise, deep knowledge of contemporary and agentic AI systems, and practical enterprise management experience.  Key Responsibilities:  Curriculum Design & Syllabi Development : Build a comprehensive 4-credit syllabus, session plans, and assignment rubrics for a twice-weekly, 1.5-hour lecture schedule.  Course Material Creation: Develop hands-on lab exercises, source-grounded research prompts, case studies, and framework guides focused on agentic AI, governance, and workflow redesign.  Assessment Framework: Design robust evaluation methods that measure both theoretical comprehension and practical application (e.g., specification-driven app building, enterprise implementation proposals).  LMS Integration: Author and organize all learning modules, reading lists, and interactive elements within Brandeis Universityâ™s Learning Management System (LMS).  Qualiï¬cations:  Education: Masterâ™s degree or Ph.D. in Business, Information Systems, Computer Science, Technology Management, or a related field.  Domain Expertise: Deep understanding of contemporary AI platforms, Large Language Models (LLMs), evaluation metrics, process control mechanisms, and agentic AI concepts (tool-use, multi-agent systems, proactive/event-triggered automation).  Teaching / L&D Experience: Demonstrated experience in graduate-level teaching, executive education, or senior-level corporate learning and development.  Technical Fluency: Ability to bridge high-level managerial strategy with technical execution (e.g., prompt engineering, low-code/specification-driven app building, workflow automation).  Preferred: Industry experience leading AI adoption, product management, or digital transformation within an enterprise setting. Familiarity with MBA curriculum standards and case-method instruction.
