AI Architect

Southern New Hampshire University

10d•Remote

About The Position

Southern New Hampshire University (SNHU) is seeking an AI Architect to join their team. This role is responsible for guiding the design, implementation, and governance of AI-powered solutions across the university's digital ecosystem. The AI Architect will align AI capabilities with institutional strategy, technology roadmaps, and business priorities, serving as a trusted advisor and technical lead for AI use cases. This position involves guiding the business through the onboarding and implementation of AI solutions, including discovery, design, and hands-on configuration to maximize value. The role also bridges the gap between Customer Success, Product, and Engineering teams, defining how AI transforms collaboration at scale. The AI Architect will orchestrate collaboration across business, data, application, and technology domains using platforms like Salesforce, ServiceNow, Workday, D2L, Banner, and O365, ensuring solutions are secure, ethical, and scalable while delivering measurable business and student outcomes. This is a remote position available in specific 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 explainability frameworks.
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.

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.
Translate institutional goals into AI solutions that deliver measurable outcomes.
Manage AI/ML architectures, data pipelines, integration, and governance.
Demonstrate strong leadership, collaboration, and consultative skills with the ability to influence at all levels.
Apply a technology-neutral mindset, intellectual curiosity, adaptability, and integrity.
Utilize a strategic mindset with a bias toward experimentation, iteration, and learning.
Perform other responsibilities as assigned.