AI Manager I

AI Tool Development Application Delivery: Leads the design, development, and deployment of AI-powered tools, applications, and workflows for campus use, with a focus on practical, high-impact solutions that advance University research, teaching, and operational objectives. Manages the full application development lifecycle from requirements gathering and prototyping through testing, deployment, and iteration. Ensures developed tools meet institutional standards for responsible AI, data privacy, accessibility, and security. Directs team members in applying AI/ML techniques, LLM integrations, API development, and software engineering best practices to deliver reliable, scalable campus solutions. Team Leadership Professional Development: Plans, directs, and evaluates the day-to-day work of a team of five AI professionals, including AI/ML engineers, developers, and applied researchers. Establishes clear performance expectations, provides ongoing coaching and feedback, and conducts formal performance evaluations. Identifies and supports individual development opportunities to build technical depth and innovation capacity across the team. Fosters a collaborative, mission-driven team environment aligned with ORAI’s responsible AI values and the University’s commitment to inclusive excellence. Campus AI Innovation Stakeholder Engagement: Identifies, prioritizes, and advances opportunities to deploy AI tools and capabilities that meet the evolving needs of campus faculty, staff, students, and administrative units. Partners with colleges, departments, and research groups to understand requirements and co-develop applied AI solutions. Communicates AI tool capabilities, limitations, and responsible use guidelines to various campus audiences. Represents AI²S/ORAI in campus working groups, advisory bodies, and innovation initiatives related to applied AI adoption. Research Software Engineering Technical Infrastructure: Applies research software engineering principles to ensure AI tools and applications are built on robust, maintainable, and interoperable technical foundations. Oversees integration of AI capabilities with existing University platforms, APIs, and research computing infrastructure, including cloud-based AI services (e.g., AWS Bedrock). Ensures documentation, version control, testing protocols, and deployment pipelines meet institutional and software engineering standards. Collaborates with the Cyberinfrastructure Systems team to align application development with underlying infrastructure capabilities. AI Governance, Responsible AI Compliance Reporting: Ensures all AI tools and applications developed by the team adhere to the University’s responsible AI framework, data governance policies, and applicable regulatory requirements. Reviews and evaluates AI solutions for bias, fairness, transparency, and alignment with ethical AI principles. Contributes to ORAI AI governance activities, policy development, and institutional reporting on applied AI initiatives. Maintains awareness of emerging AI technologies, regulatory developments, and peer institution practices to inform continuous improvement of the team’s approach. Knowledge, Skills and Abilities: Practical knowledge of AI/ML concepts, techniques, and application development, including large language models (LLMs), generative AI, predictive modeling, and data analysis. Knowledge and understanding of research software engineering principles, software development lifecycles, and technical documentation standards. Knowledge of responsible AI frameworks, data privacy regulations (e.g., FERPA, HIPAA applicability), and institutional AI governance practices. Knowledge and understanding of cloud AI platforms, API ecosystems, and integration patterns for enterprise AI tool deployment. Knowledge and understanding of responsible AI principles, data privacy regulations, and AI governance frameworks. Strong applied AI and software development skills, with demonstrated ability to move from concept to working application. Effective team leadership and people management skills, including performance coaching, goal-setting, and staff development. Ability to provide clear and accessible communication skills, including the ability to explain AI capabilities and limitations to non-technical campus stakeholders. Project management and prioritization skills, with the ability to manage multiple concurrent initiatives in a dynamic environment. Proficiency in AI/ML frameworks and tools (e.g., Python, LangChain, OpenAI/Anthropic APIs, Hugging Face, or equivalent) and software development practices including version control, CI/CD, and API development. Ability to identify high-impact opportunities for AI tool adoption and translate campus needs into practical, responsible AI solutions. Ability to build collaborative relationships across varioius university stakeholders, including faculty, staff, administrators, and technical teams. Ability to stay current with rapidly evolving AI technologies and evaluate their applicability and responsible use in a university context. Ability to cultivate an innovative, and mission-aligned team culture consistent with ORAI’s responsible AI values.