Job Description Insight Global is seeking an AI Platform Engineer to help build, integrate, and support enterprise AI services for the one of our top higher education clients. This role is focused on turning AI capabilities into real services people can use. The engineer in this position will help design and operate secure, scalable, and supportable AI platform offerings that fit into the way our client works. That includes identity and access, automation, governance, cloud integration, operational readiness, and user enablement. The AI Platform Engineer will work across public cloud platforms, enterprise applications, and emerging AI products to move new capabilities from pilot to production. This role partners closely with teams across enterprise infrastructure, security, identity, ITSM, and other ITS and University stakeholders. Key Responsibilities Design, implement, support, and improve enterprise AI platforms and services. Build and maintain the technical foundations for AI services, including access, provisioning, automation, logging, monitoring, and operational readiness. Support AI-related engineering across UVAs cloud and enterprise technology environments. Develop reusable patterns for onboarding, integration, access control, lifecycle management, and service delivery. Build automation and infrastructure-as-code to improve consistency and scale. Support evaluation, pilot, rollout, and ongoing operations for AI platform capabilities and integrations. Produce technical documentation, runbooks, knowledge articles, and reference materials. Pay Range: $30-$65/HR We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce : Skills and Requirements Bachelors degree in computer science, information systems, engineering, or a related field, or equivalent combination of education and experience. Demonstrated hands-on experience using large language models (LLMs) and generative AI platforms in technical, engineering, or operational work. Experience implementing, integrating, supporting, or evaluating generative AI services in a production, pilot, or enterprise setting. Experience with one or more AI platforms or services such as Microsoft Copilot Studio, Azure OpenAI, Azure AI services, Amazon Bedrock, Google AI services, OpenAI enterprise offerings, Anthropic/Claude, AI gateways, or similar technologies. Experience with AI-related APIs, prompt-driven workflows, orchestration patterns, or platform integrations. Experience supporting enterprise platforms, infrastructure, or cloud services in production environments. Experience with one or more public cloud platforms such as Microsoft Azure, AWS, or GCP. Experience with enterprise identity, authentication, access management, directory integration, or single sign-on. Experience with scripting, automation, or infrastructure-as-code using tools such as Python, PowerShell, Bash, Terraform, Bicep, or similar technologies. Strong troubleshooting, documentation, and cross-team collaboration skills. Experience with shared-service delivery, platform operations, or service onboarding in a large and complex organization. Experience integrating SaaS or enterprise applications, including app registration, enterprise app onboarding, SCIM, SSO, admin consent, or API-based integration. Experience supporting developer enablement or AI-assisted engineering workflows. Familiarity with higher education technology environments. Experience balancing innovation with governance, operational maturity, and long-term supportability.

Candidates should possess a Bachelor's degree in computer science, information systems, engineering, or a related field, or an equivalent combination of education and experience. Demonstrated hands-on experience with large language models (LLMs) and generative AI platforms in technical, engineering, or operational capacities is required. Experience implementing, integrating, supporting, or evaluating generative AI services in a production, pilot, or enterprise setting is also necessary. Proficiency with one or more AI platforms or services such as Microsoft Copilot Studio, Azure OpenAI, Azure AI services, Amazon Bedrock, Google AI services, OpenAI enterprise offerings, or Anthropic/Claude is expected. Experience with AI-related APIs, prompt-driven workflows, orchestration patterns, or platform integrations is also a requirement.