AI Architect

Southern New Hampshire University

9d•Remote

About The Position

The AI Architect will report to the Vice President of Technology and Business Enablement. In this role, you will be a business and expert who guides the design, implementation, and governance of AI-powered solutions across the university's digital ecosystem. You will align AI capabilities with institutional strategy, technology roadmaps, and business priorities. You'll serve as a trusted advisor and technical lead on AI use cases ranging from intelligent agents to workflow automation. You will guide the business throughout the onboarding and implementation of our multiple AI solutions. You'll guide through the discovery, design, and hands-on configuration of AI-powered features, ensuring that the maximum value from AI capabilities supports outcomes. You will also bridge the gap between Customer Success, Product, and Engineering teams, helping define how AI transforms collaboration at scale—across the SNHU's broader tech ecosystem. The AI Architect will orchestrate collaboration across business, data, application, and technology domains, using platforms such as Salesforce, ServiceNow, Workday, D2L, Banner, and O365. You will balance innovation with compliance, ensuring solutions are secure, ethical, and scalable, while delivering measurable business and student outcomes. You will work remotely from any of our approved states.

Requirements

15+ years in the technology industry.
8+ years of experience in IT architecture.
3+ years in AI/ML solution design and delivery.
Experience integrating AI solutions with enterprise platforms (e.g. Salesforce, ServiceNow, Workday, D2L, Banner, or equivalent).
Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch), cloud platforms (Azure, AWS, GCP), and big data technologies.
Hands-on experience designing or implementing AI solutions, including working with LLMs, prompt engineering, and agent frameworks (e.g. AutoGPT, LangChain, RAG)
Experience with system integration, APIs, cloud services, and enterprise data management.
Experience with enterprise architecture frameworks (TOGAF, Zachman) and agile delivery.
Experience with ethical AI, bias mitigation, and explain ability frameworks.

Responsibilities

Partner with business and technology partners to identify AI opportunities that support student success, operational efficiency, and digital business models.
Align AI programs with enterprise strategies, roadmaps, and higher education best practices.
Provide guidance on how AI, ML, and automation will improve current and future-state architectures.
Define, design, and oversee AI architectures that integrate with core enterprise platforms (Salesforce, ServiceNow, Workday, D2L, Banner, O365).
Collaborate with business architects, data architects, and developers to source, govern, and manage data for AI solutions.
Lead evaluation, selection, and implementation of AI/ML models, frameworks, and platforms.
Ensure architectures account for privacy, compliance (FERPA, HIPAA, GDPR), and security standards.
Establish MLOps practices, including CI/CD for AI models, automated testing, validation, and deployment.
Embed MCP (Model Control & Performance) practices: lifecycle management, retraining, drift detection, and decommissioning.
Oversee deployment, monitoring, and lifecycle management of AI solutions.
Contribute to enterprise AI governance frameworks, standards, and policies.
Establish metrics and monitoring approaches to track AI model performance, bias, and risk.
Implement adversarial AI defense and secure AI infrastructure (encryption-in-use, multi-tenant isolation).
Ensure compliance with ethical AI practices, accessibility standards, and institutional values.
Promote AI capabilities across the institution; facilitate workshops, proofs-of-concept, and demos.
Provide consultative support to enterprise architects, application teams, and business leaders.
Mentor technical teams on AI patterns, frameworks, and best practices.
Enable multi-agent orchestration frameworks (LangChain, AutoGPT, RAG) and ensure agent interoperability across platforms
Ability to translate institutional goals into AI solutions that deliver measurable outcomes.
Deep understanding of AI/ML architectures, data pipelines, integration, and governance.
Strong leadership, collaboration, and consultative skills with the ability to influence at all levels.
Technology-neutral mindset, intellectual curiosity, adaptability, and integrity.
Strategic mindset with a bias toward experimentation, iteration, and learning
Other responsibilities as assigned