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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Enterprise AI Architect - **Company:** Southern New Hampshire University - **Location:** United States (Remote available) - **Experience:** Experienced - **Salary:** $137,839.0 - $220,582.0 - **Contract:** Permanent contract - **Skills:** Microsoft Windows, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cyber Security, Continuous Integration, Desire2Learn, Enterprise Architecture Framework, Machine Learning, Tensorflow, Salesforce.Com, Software Engineering, Systems Integration, Zachman Framework, Enterprise Data Management, Google Cloud, Enterprise Software Applications, Pytorch, Office365, Large Language Models, IT Architecture, Generative AI, Togaf, Information Technology, Banner Advertisement, Data Analytics, Data Management, Machine Learning Operations, Workday, Servicenow, Microservices - **Published:** July 9, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=a23bb1f71add4c2f ## About the Role * 15+ years in information Technology. technology, including: * 8+ years in enterprise or solution architecture. * 3+ years in AI/ML solution design and delivery. * Experience integrating AI solutions with enterprise platforms (e.g., Salesforce, ServiceNow, Workday, D2L, Banner). * Experience with enterprise architecture frameworks (e.g., TOGAF, Zachman) and Agile delivery. * Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), LLMs, and agent-based architectures (e.g., RAG, AutoGPT, LangChain). * Experience with Cloud platforms (Azure, AWS, GCP) and data/AI pipeline design. * Experience with APIs, microservices, system integration, and enterprise data management. * Experience with ML Ops/LLM Ops practices including CI/CD, monitoring, and deployment patterns across (Azure, AWS, GCP). * Experience with enterprise standards for principles, patterns and guidelines on the use of AI within the SNHU environment. Inclusive of alignment with Responsible AI standards and Sustainability goals. ## Description The Enterprise AI Architect reports to the Vice President of Enterprise Architecture and serves as the technical and strategic lead for AI capabilities across the university's digital ecosystem. This role ensures AI solutions align to enterprise strategy, architecture standards, and business priorities while delivering secure, scalable, and ethical outcomes. The architect partners across business, IT, and data domains to define and implement AI-enabled capabilities-including generative AI, machine learning, automation, and advanced analytics-integrated into core enterprise platforms (e.g., Salesforce, ServiceNow, Workday, D2L, Banner, O365). 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. Key Relationships: * Enterprise Architecture * Application Development and Engineering * Data & Analytics * Cloud and Infrastructure * Cybersecurity * Product Management * Enterprise Applications (Salesforce, Workday, Banner, D2L, ServiceNow, Microsoft 365) * Integration and Platform Teams * AI Engineering Team You will work 100% remotely from any of our approved states. #LI-Remote What You'll Do: * Define and evolve enterprise AI architecture, standards, reference models and implementation guidelines to support consistent solution delivery across business functions. * Align AI initiatives to enterprise strategies, roadmaps, and business priorities. * Identify and prioritize AI opportunities that drive student success and operational efficiency. * Design scalable AI platforms and solutions across data, application, and technology domains. * Provide guidance on how AI, ML, and automation will improve current and future-state architectures. * Lead design and implementation of AI-powered solutions (e.g., LLMs, agents, automation, and analytics). * Integrate AI capabilities with enterprise applications and data platforms. * Guide evaluation and selection of AI/ML models, frameworks, and vendors. * Establish reusable patterns, APIs, and integration approaches. * Establish governance practices covering model oversight, responsible AI usage, security controls, compliance expectations, and lifecycle management. * Establish AI governance, including responsible AI, security, privacy, and compliance (FERPA, HIPAA, GDPR). * Establish lifecycle management practices (MLOps/LLMOps, model monitoring, drift detection, retraining). * Implement performance, bias, and risk monitoring frameworks. * Ensure secure AI architecture (e.g., data protection, isolation, adversarial defense). * Partner with business, product, data, and engineering teams to provide AI solutions. * Provide architectural guidance to architects and delivery teams. * Facilitate workshops, POCs, demos and AI adoption projects identifying viable opportunities where AI can be a positive differentiator. * Mentor teams on AI best practices, patterns, and frameworks ## Related Videos - [Destigmatizing the Workplace: Building Real Inclusion](https://www.wearedevelopers.com/videos/1492-destigmatizing-the-workplace-building-real-inclusion) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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