Job Description The Enterprise Solutions & Enabling Technologies (ESET) unit within the Division of IT at Virginia Tech is working to ensure that faculty, staff, and students at the university have access to robust tools and environments to empower innovation and collaboration at all levels. To support this mission, ESET is seeking a talented AI Infrastructure Engineer to join our team. The AI Infrastructure Engineer is responsible for the technical deployment, configuration, integration, and ongoing engineering support of Virginia Tech’s enterprise generative AI platform. This role sits within the Collaborative Computing Solutions (CCS) department within ESET and provides the hands-on cloud engineering expertise needed to operate the university’s AI environment at scale. The engineer ensures the platform is securely implemented in the Virginia Tech Azure tenant, integrates with institutional identity and data systems, and leverages Azure AI Foundry, HPC hosted models, and cross cloud model endpoints. The role supports platform enhancements, model onboarding, RAG capabilities, monitoring, and advanced technical troubleshooting. This role also ensures Virginia Tech can responsibly adopt generative AI at scale by building the secure, compliant, and high performance platform that powers university wide teaching, research, and administrative use cases. In its first year, this role will focus on standing up and stabilizing the “Hokie AI” platform, onboarding initial production models and RAG data sources, establishing monitoring and cost controls, and serving as the primary technical owner for the platform as it transitions from pilot to enterprise service. CCS directly manages the following services for Virginia Tech: - University Email Services (Gmail and Exchange Online) - VT Collaborative Software as a Services (SaaS) Environments (Google Workspace, Microsoft 365, and Slack) - Cloud Accounts and Services (Amazon Web Services, Google Cloud Platform, and Microsoft Azure) - Secure Virtual Environments (Hyper V virtual machines) - VT Active Directory Services - University AI Platform Management Responsibilities: Platform Deployment & Engineering - Implement and configure the Hokies AI platform within the Virginia Tech Azure tenant using Azure AI Foundry and Azure cloud services, following best practices for resilient deployment. - Build and maintain the platform infrastructure at the subscription level, including resource provisioning, networking, storage, key vaults, and logging. - Engineer integrations with Microsoft Entra ID for authentication, role assignment, and Grouper based access control. - Works from established architectural patterns and governance guidance defined by CCS leadership, Security Office, and the AI Working Group. Model Integration & Federation - Integrate LLMs hosted through Azure AI Foundry as well as models hosted on VT’s HPC infrastructure using REST endpoints. - Contribute to the roadmap and technical readiness for future multi-cloud model connectors (AWS, GCP), in partnership with CCS leadership and vendors. - Assist with onboarding new models, model versions, and domain specific finetuned models. RAG / Data Source Engineering - Implement connectors for RAG sources including OneDrive, SharePoint, Google Drive, local uploads, and future Snowflake integrations. - Ensure RAG indexes, embeddings, and caches remain fully inside VT’s Azure environment. - Engineer retention, deletion, and storage workflows according to VT data governance requirements. - This role focuses on the platform mechanics of RAG (connectors, indexing, retention, access control), not on curating or managing institutional content. Content ownership and accuracy remain the responsibility of the data-source owners. Monitoring, Observability & Performance - Build dashboards and monitoring pipelines using Azure Monitor, Log Analytics, or platform native tools. - Implement throttling, alerting, quota enforcement, and cost visibility mechanisms. - Diagnose performance issues, latency, and model availability problems. Security, Compliance & Guardrails - Configure logging, auditing, access control, guardrail policies, and prompt filtering mechanisms. - Ensure all data—logs, histories, RAG data, metadata—remain in US only Azure regions. - Implement and maintain technical controls that support FOIA, eDiscovery, and records retention workflows in coordination with compliance stakeholders. - Ensure the platform aligns with Virginia Tech's responsible AI principles, transparency expectations, and institutional governance policies. Technical Support & Troubleshooting - Serve as Tier3 engineering escalation for issues routed through 4Help/UEE. - Work with the vendor on deep technical issues, bug reports, and platform level fixes. - Support sandbox environments for testing new features, models, and configurations. Advanced Use Cases & Research Enablement - Assist researchers and faculty with API access, custom agent environments, and integration of research centric datasets. - Support Innovation Fund pilot projects requiring platform extensions or novel integrations. Please note: Sponsorship is not available for this position. Required Qualifications - Masters degree in computer science, information systems, IT-related field, or equivalent combination of education and significant professional experience. - Strong hands-on experience with Microsoft Azure, including resource groups, VNets, monitoring, identity integration, and experience deploying AI/ML services (Azure AI Foundry or equivalent platforms). - Experience with LLMs, containerized services, AI deployment patterns, or vector databases. - Understanding of SAML/OIDC/OAuth2/Entra ID identity flows and group based authorization. - Experience with Python, REST APIs, automation, and infrastructure scripting. - Familiarity with cloud logging, monitoring, cost controls, and governance frameworks. - Ability to translate security, compliance, and data classification needs into technical configurations. Preferred Qualifications - Experience with higher education IT environments. - Azure certifications (e.g., AZ 104, AZ 305, AI 102). - Experience integrating HPC hosted AI models or GPU backed inference endpoints. - Experience with RAG pipelines and document embeddings. - Experience engineering platforms requiring WCAG accessibility support. - Experience operating shared platforms that balance research flexibility with enterprise security and cost controls. - Strong understanding of cost optimization for AI workloads - Experience with prompt safety, guardrails, or LLM evaluation tooling Overtime Status Exempt: Not eligible for overtime Appointment Type Regular Salary Information $100,000 - $130,000 Hours per week 40 Review Date 3/18/2026 Additional Information The successful candidate will be required to have a criminal conviction check. About Virginia Tech Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including Blacksburg, the greater Washington, D.C. area, the Health Sciences and Technology Campus in Roanoke, sites in Newport News and Richmond, and numerous Extension offices and research institutes. A leading global research institution, Virginia Tech conducts more than $650 million in research annually. Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance. These valuable contributions to university shared governance provide important representation and perspective, along with opportunities for unique and impactful professional development. Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law. If you are an individual with a disability and desire an accommodation, please contact IT Human Resources at ithr@vt.edu during regular business hours at least 10 business days prior to the event.