Overview
Skills
Job Details
Required Qualifications
Experience designing and evaluating AI/machine learning (ML) solutions, including natural language processing (NLP), ML workflows, and model deployment strategies.
Experience working with nontechnical users responsible for functional requirements and translating technical language/concepts in lay terms.
Hands-on experience with cloud-based AI services, such as Amazon Web Services (AWS) Sage Maker, Microsoft Azure Machine Learning, or Google Cloud Vertex AI, including managing infrastructure, training pipelines, and inference endpoints.
Ability to review and contribute to procurement documentation (e.g., requests for proposals (RFPs), technical requirements) and to assess vendor responses for alignment with architectural, scalability, and compliance standards.
In-depth knowledge of API-based integrations, data exchange formats (e.g., Representational State Transfer [REST], JavaScript Object Notation [JSON], Extensible Markup Language [XML]), and interoperability between AI tools and enterprise systems like learning management systems (LMSs) or identity management platforms.
Familiarity with education-sector data privacy requirements (e.g., Family Educational Rights and Privacy Act [FERPA]), AI governance best practices, and secure handling of student data within AI-enabled environments.
Preferred/Desired Qualifications
AWS, Google Cloud Platform (Google Cloud Platform), Azure, or The Open Group Architecture Framework (TOGAF).