AI Engineer

USG Corporation•Chicago, IL

17h

About The Position

The AI Engineer plays a pivotal role in USG’s digital transformation by designing, developing, and delivering enterprise-class artificial intelligence solutions that accelerate innovation and optimize business processes. This role has a strong emphasis on building integrated, AI-enabled applications—connecting models, data, and workflows across enterprise platforms through well-designed APIs and secure system integrations. The AI Engineer will leverage technical expertise to build and deploy Azure-based AI platforms, utilizing modern containerization strategies to enable scalability and reliability. The AI Engineer collaborates closely with cross-functional teams (IT, business units, and external partners) to identify AI opportunities, translate business challenges into practical technical solutions, and deliver applications that integrate seamlessly with existing systems (identity, data, ERP/CRM, and other line-of-business platforms). The AI Engineer will drive adoption by creating prototypes and production-grade services, establishing integration patterns and reusable components, and leading internal upskilling initiatives. This position requires a passion for emerging technologies, a creative problem-solving mindset, and the ability to rapidly learn and apply new methods in a rapidly evolving technology landscape. The AI Engineer is also responsible for ensuring that deployments adhere to best practices in security, privacy, and compliance, and for proactively monitoring and optimizing solution performance.

Requirements

Deep proficiency in Azure AI services and infrastructure.
Strong experience with containerization (Docker/Kubernetes) for scalable application and AI deployments (AKS preferred, not required).
Experience designing and implementing integrations between services and enterprise applications (API design, authentication/authorization, and data exchange patterns).
Familiarity with Microsoft 365 Copilot and Copilot Studio for designing and deploying copilots/agents aligned with security, compliance, and enterprise integration standards.
Advanced scripting and programming skills for AI development.
Excellent collaboration, interpersonal, and problem-solving skills.
Ability and motivation to quickly pick up new technologies and adapt in a rapidly changing environment.
Strong understanding of IT and data security requirements.
Bachelor’s Degree in Computer Science or related field (or equivalent experience)
2-5 years of experience building and deploying AI solutions and/or integrated applications in hybrid cloud environments.
Practical experience with infrastructure as code for cloud and hybrid environments (for example, using Terraform, ARM templates, or similar).
Hands-on experience integrating cloud services with enterprise applications (API management, event-driven integration, and secure service-to-service communication).

Nice To Haves

Exposure to Kubernetes on Azure (AKS) is a plus.
Experience with Microsoft 365 Copilot and/or Copilot Studio is a plus.
Advanced programming and scripting skills (Python is highly preferred; experience with C# is a plus).
Familiarity with Open Web UI and MCP Tooling is a plus.
Experience promoting AI literacy—such as leading internal workshops, developing documentation, or mentoring colleagues on AI concepts and practices.

Responsibilities

Architect and deploy AI/ML models and solutions on Azure and other cloud platforms.
Promote and lead AI literacy efforts through training and documentation for staff.
Develop and deploy containerized AI-enabled applications and services using technologies such as Docker and Kubernetes (AKS is preferred but not required).
Evaluate, select, and integrate cloud-based AI technologies, ensuring they align with application architecture and enterprise integration standards.
Design, build, and support integrations between AI services and enterprise applications using APIs (REST/Graph), messaging/eventing, and secure connectivity patterns.
Experience enabling Microsoft Copilot capabilities (e.g., Microsoft 365 Copilot) and building solutions with Copilot Studio (agents, integrations/connectors, and governance).
Implement application operational best practices (logging, monitoring, alerting, scalability, and reliability) for integrated AI services in production.
Collaborate with other IT specialists and business units to identify opportunities for AI-driven automation and improvement.
Implement CI/CD pipelines for AI applications and services.
Ensure industry standards are followed for data privacy and IT security.
Monitor, evaluate, and optimize the performance and reliability of AI solutions.
Provide technical leadership and mentorship around AI adoption.
Review emerging trends in enterprise AI and provide short- and long-term technology roadmaps.