Employment Opportunities

AI Adoption Specialist

Apply now Job No: 503070
Work Type: Staff Full Time (1500 hours or greater)
Location: Dayton, OH
Category: University Staff
Department: Academic Technologies - 804700
Pay Grade: B - Exempt
Advertised:
Applications close:

Position Summary:

Join the University of Dayton's innovative UDit division and help shape the future of artificial intelligence in higher education! We're seeking a dynamic AI Adoption Specialist to lead our institution's strategic integration of AI technologies across academic and administrative operations.

You'll enjoy comprehensive benefits including excellent health coverage, generous retirement contributions, and tuition assistance for you and your family. Our beautiful 423-acre campus provides state-of-the-art facilities, while Dayton's affordable cost of living and vibrant community offer an outstanding quality of life.

The primary responsibilities of the AI Adoption Specialist include developing and implementing comprehensive testing frameworks, quality assurance protocols, and performance validation processes for AI agents and agentic workflows. This role will focus on ensuring the reliability, accuracy, and effectiveness of AI-driven solutions through systematic testing, optimization, and monitoring. Additionally, the role includes designing training programs for AI adoption, creating documentation standards, and establishing best practices for AI quality assurance.

This position requires strong analytical skills, experience in software testing methodologies, and an understanding of AI systems and their operational requirements. The AI Adoption Specialist serves as a member of the AI Applications and Services team in UDit, reporting to the Director of AI Applications and Services. This position is critical to maintaining the highest standards of AI system performance and ensuring the successful adoption of AI technologies throughout the university community.

Minimum Qualifications:

1. At least 2 years of experience in software testing, quality assurance, or system validation.
2. Hands-on experience with testing tools and methodologies, including automated testing frameworks.
3. Understanding of software testing principles, test case design, and quality assurance best practices.
4. Exposure with AI systems, large language models, and agent-based architectures.
5. Excellent analytical and problem-solving abilities with strong attention to detail.
6. Strong communication skills and the ability to effectively document technical processes and training materials.

Preferred Qualifications:

While not everyone may possess all of the preferred qualifications, the ideal candidate will bring many of the following:

1. Bachelor's Degree in Computer Science, Information Systems, Software Engineering, or a related technical field.
2. At least 3 years of experience in quality assurance, software testing, or AI system validation.
3. Experience with AI agent testing, performance monitoring, and workflow optimization.
4. Familiarity with training program development and adult learning principles.
5. Experience in higher education technology environments.
6. Proficiency with testing automation tools, performance monitoring systems, and CI/CD pipelines.
7. Ability to effectively collaborate with diverse teams and facilitate training sessions.

Special Instructions to Applicants:

To apply please submit a cover letter addressing each minimum qualification and any applicable preferred qualifications that you meet.

Applicants must be currently authorized to work in the United States on a full-time basis. The University does not provide work visa sponsorship for this position.

Closing Statement:

Informed by its Catholic and Marianist mission, the University is committed to the principles of diversity, equity, and inclusion. Informed by this commitment, we seek to increase diversity, achieve equitable outcomes, and model inclusion across our campus community. As an Affirmative Action and Equal Opportunity Employer, we will not discriminate against minorities, women, protected veterans, individuals with disabilities, or on the basis of age, race, color, national origin, religion, sex, sexual orientation or gender identity.

 

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