AI Engineer

AI Engineer Job Summary

Artificial Intelligence (AI) / Machine Learning (ML) Engineers The Utah Data Coordinating Center (DCC) is seeking an experienced AI Engineer to design, build, and operate secure, scalable AI-enabled research platforms. This role sits at the intersection of machine learning, cloud infrastructure, and regulated research environments, supporting national and international research programs. You will work closely with research IT leadership, data engineers, security teams, and external partners to operationalize AI workflows while maintaining strong governance, security, and compliance standards.

This is a hands-on engineering role for someone who enjoys building real systems, not prototypes that live on slides. This position will report to the Sr. Supervisor, IT.

• Design and deliver end-to-end hybrid data and AI solutions
  Collaborate with data scientists, engineers, and business stakeholders to design, build, test, deploy, and support scalable data pipelines and AI/ML models across hybrid cloud and on-premises environments. Deliver reliable, production-ready solutions aligned with organizational strategy and enterprise architecture standards.
• Operationalize machine learning systems using modern MLOps practices
  Partner with cross-functional teams to deploy, monitor, and manage ML models through CI/CD pipelines, model versioning, experiment tracking, automated testing, and lifecycle management frameworks. Support both batch and real-time inference workloads while ensuring reliability, scalability, and maintainability.
• Build and maintain secure, scalable infrastructure across hybrid environments
  Implement containerized and cloud-native solutions using Docker and orchestration platforms (e.g., Kubernetes) to support data and AI workloads. Apply infrastructure-as-code (IaC) and automation practices to enable reproducibility, scalability, and operational efficiency across on-premises and cloud systems.
• Ensure secure, compliant, and governed data and AI systems
  Collaborate with security and compliance teams to implement role-based access controls, encryption, network security controls, and audit logging across environments. Align architectures with regulatory frameworks (e.g., HIPAA, NIST, FISMA) and enterprise governance standards while promoting responsible AI practices.
• Translate business requirements into scalable technical architectures
  Engage with stakeholders to understand strategic objectives and convert them into robust data architectures, algorithms, and automation workflows. Promote shared ownership of solutions, ensuring alignment with long-term sustainability, performance expectations, and enterprise standards.
• Monitor, optimize, and sustain production systems
  Implement monitoring, logging, and alerting frameworks to track data pipeline health, model performance, data drift, system reliability, and cost efficiency. Apply performance tuning, reliability engineering, and continuous improvement practices to maintain operational excellence.
• Communicate technical designs and analytical insights clearly
  Document system architectures, data flows, AI workflows, and operational procedures. Present complex technical concepts and model outcomes to both technical and non-technical stakeholders in a clear and actionable manner.
• Advance engineering excellence and innovation
  Stay current with emerging technologies in data engineering, cloud computing, and applied AI. Evaluate and adopt new tools and methodologies that improve automation, scalability, security, and organizational impact while adhering to best practices and architectural standards.

To learn more about the Utah DCC visit (Use the "Apply for this Job" box below)./UtahDCC

This position is not eligible for work visa sponsorship.

The University of Utah offers a comprehensive benefits package. You can learn more about the great benefits of working for the University of Utah h.edu

Artificial Intelligence (AI) / Machine Learning (ML) Engineer Research, design, develop, test, and support artificial intelligence (AI) and machine learning (ML) frameworks and models. Leverage AI/ML techniques to answer business questions, support…