Part-time Faculty Workforce Development Continuing Education (WDCE) AI Agent/Prompt Engineering Instructor at Montgomery College in Montgomery County, MD

Job description

Montgomery College accepts applications for Adjunct/Part-time Faculty on a continuous basis. Applications may be reviewed periodically based on the student enrollment needs. The listing of a course in the schedule of classes as “TBA” does not constitute an assignment. The hiring decision for part-time faculty involves an academic judgment and shall be determined at Management’s sole discretion. Job Description Montgomery College, Workforce Development Continuing Education, is currently accepting applications for possible openings as a part-time faculty member teaching AI Agents and/or Prompt Engineering. We are seeking an enthusiastic and dedicated teacher who exhibits a high degree of professionalism, a strong commitment to our students, and demonstrates the ability to motivate and educate in an engaging manner. ***Montgomery College accepts applications for Adjunct/Part-time Faculty on a continuous basis . Applications may be reviewed periodically based on student enrollment needs. *** The listing of a course in the schedule of classes as “TBA” does not constitute an assignment. The hiring decision for part-time faculty involves an academic judgment and shall be determined at Management’s sole discretion. Duties and Responsibilities: Deliver hands-on, skills-based instruction on AI Agents or Prompt Engineering aligned with course objectives and industry standards. Teach adult students how to design, build, and deploy AI agents using modern tools, frameworks, and APIs. Incorporate leading generative AI platforms such as Claude into instruction, emphasizing real-world applications. Teach students how to craft, refine and evaluate effective prompts for large language models, covering prompt design techniques, iterative testing, and best practices for reliable AI outputs. Prepare adult learners for careers in AI, automation, and data-driven roles. Facilitate courses in-person and/or remotely during weekday evenings or Saturdays. Collaborate with program staff and faculty on curriculum development and updates. Maintain accurate attendance records and submit administrative tasks promptly. Provide students with effective support, communication, and timely feedback. Required Qualifications: Bachelor’s degree in Computer Science, Information Systems, or a related discipline. Strong communication skills and a passion for teaching adult learners. Demonstrated expertise in artificial intelligence concepts, including AI agents, automation workflows, prompt engineering, and API integrations. Professional experience working with generative AI tools such as Claude or similar large language model platforms. Ability to teach hands-on, project-based content related to building and deploying AI-driven solutions. Able to teach in person. Dependable, punctual, and committed to student success. Successful candidates will have a demonstrated commitment to promoting belonging, inclusion, and multicultural competence in an educational and work environment and must be willing to contribute to the College’s strategic plan of inclusion. Faculty members are expected to have access to a personal computer with virus protection that can connect to the internet outside of the work location (i.e., office, classroom, college campus)*. Montgomery College (MC) provides an MC e-mail account and access to the learning platform, password-protected faculty sections of the website, college listservs, and other faculty communications tools. * If you do not have access to a personal computer, please notify the department chair at the time of the interview. Subject to available funds, the college may be able to provide temporary access to resources. Must be eligible to work in the United States without a sponsor. Preferred Qualifications: Prior teaching or training experience (community college or workforce development environment a plus) Experience delivering instruction in hybrid, in-person, and online modalities. Familiarity with Learning Management Systems (e.g., Bl