AI DevOps Engineer

Job DescriptionPosition Purpose:As a UW employee, you have a unique opportunity to change lives on our campuses, in our state, and around the world. UW employees offer their boundless energy, creative problem-solving skills, and dedication to build stronger minds and a healthier world. By being deeply invested in our work, showing compassion in our interactions, and embodying the spirit of a team player, each member contributes to a thriving community. UW is committed to attracting and retaining a diverse staff; your experiences, perspectives, and unique identities will be honored at the University of Washington. Together, our community strives to create and maintain working and learning environments that are inclusive, equitable, and welcoming.University of Washington is at the forefront of leveraging cutting-edge technologies to transform education, research and healthcare. UW Information Technology (UW-IT) is the central IT organization for the University of Washington, collaborating with partners across the University community to advance teaching, learning, innovation and discovery. UW-IT delivers critical IT services and support to all three campuses, UW medical centers and global research operations. Innovation and discovery are at the heart of what UW-IT does and drive the work in advancing the University of Washington's role and mission.We are seeking an innovative and experienced AI DevOps Engineer to support the artificial intelligence (AI) initiatives at the university and its three campuses. This role is a pivotal role in shaping and implementing our AI strategy to transform UW into an AI-powered University. As a core technical member of the AI Platforms team, the AI DevOps Engineer drives the engineering, deployment, administration, and quality assurance of AI-powered applications and services across the university. The AI DevOps Engineer role will work within Service Management and AI Platform team under the UW's IT infrastructure Umbrella that provides critical technology support to all three campuses, UW Medicine, and research operations around the world. Position ComplexitiesThe AI DevOps Engineer role requires a strong technical foundation spanning cloud engineering, infrastructure-as-code, CI/CD pipeline development, application administration, and QA/release management within a Microsoft Azure–centric environment. Deep hands-on expertise in Azure architecture, identity and access management, networking, container orchestration, and platform-native services is essential to ensure secure, reliable, and scalable delivery of AI applications across the university. This role balances engineering velocity with operational stability, security, and cost optimization while maintaining high standards for automation, monitoring, and platform governance.Success in this position also depends on the ability to operate effectively within a decentralized and complex institutional environment. The AI DevOps Engineer must collaborate across AI research, development, IT operations, and information security teams to promote consistent DevOps practices, strengthen release discipline, and align cloud implementations with institutional strategy. Strong communication, proactive risk management, and continuous improvement are critical to maintaining resilient, compliant, and high-performing AI platform services.Position Dimensions and Impact to the UniversityThe AI DevOps Engineer serves as a key technical contributor on the AI Platforms team, responsible for the engineering, deployment, administration, and quality assurance of AI applications and services at the university. This role combines a strong engineering foundation with hands-on application administration, deep Microsoft Azure cloud platform expertise, and QA/release management practices to ensure reliable, secure, and scalable delivery of AI solutions. The AI DevOps Engineer works collaboratively with cross-functional teams to build and maintain CI/CD pipelines, manage cloud infrastructure, administer AI platform applications, and drive continuous improvement in development and release processes.  Position Responsibilities[25%] Engineering & Development-Design, develop, and maintain infrastructure-as-code (IaC) solutions using tools such as Terraform, Bicep, or ARM templates to provision and manage Azure cloud resources for AI platforms and services.-Build and maintain CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) to automate the build, test, and deployment of AI applications and microservices.-Develop scripts, automation tools, and utilities (e.g., PowerShell, Python, Bash) to streamline operational tasks, monitoring, and incident response.-Collaborate with AI developers and data engineers to containerize applications (Docker, Kubernetes/AKS) and optimize deployment architectures for performance and cost efficiency.-Contribute to the development of APIs, integrations, and middleware that connect AI services with existing university IT systems and data sources.-Participate in code reviews, pair programming, and technical design discussions to maintain high engineering standards across the team.[25%] Application Administration & Azure Platform Management-Administer and maintain AI platform applications, including configuration management, user access provisioning, patching, upgrades, and performance tuning.-Manage and monitor Azure cloud environments (e.g., Azure App Services, Azure AI Services, Azure SQL, Azure Storage, Azure Virtual Networks) ensuring availability, security, and compliance with university policies.-Implement and manage identity and access management (IAM) solutions using Azure Active Directory (Entra ID), role-based access controls, and conditional access policies.-Monitor application and infrastructure health using Azure Monitor, Log Analytics, Application Insights, and other observability tools; triage and resolve incidents promptly.-Manage Azure resource costs through rightsizing, reserved instances, and