Virtual - Arizona, United States of America · 2 days ago
Design, deploy and support scalable ML, LLM and RAG pipelines in cloud environments, including CI/CD, monitoring, retraining and rollback. Partner with data scientists and engineers to keep production AI systems reliable and compliant.
Primary City/State: Virtual Arizona Category: Data Intelligence Shift: Day Department: Augmented Intelligence Hours: Monday-Friday Days Location: Remote -- Must be located in Arizona -- Occasional on site as needed. Great care starts with great people. (Like you.) At HonorHealth, you’ll find something special. From humble beginnings in 1927 to one of Arizona’s largest nonprofit healthcare systems, our culture is built on warmth and neighborly kindness. Behind every smile is a highly skilled professional with deep expertise and an unwavering dedication to what matters most — caring for the health and well-being of people and communities across the greater Phoenix area. Responsibilities: JOB SUMMARY The AI / ML DevOps Engineer designs, develops, deploys, and supports scalable machine learning solutions that enable advanced analytics and AI capabilities across HonorHealth. This role operationalizes models and pipelines, monitors performance, and partners with data, engineering, and stakeholders to deliver reliable solutions aligned to governance and data handling expectations. The role partners closely with data engineers, data scientists, AI model developers, platform teams, and business stakeholders to translate complex needs into production-ready deployments, monitor ongoing performance, and continuously improve AI/ML capabilities aligned to governance and operational standards. ESSENTIAL FUNCTIONS Design and implementation of the environment that deploys scalable AI/ML solutions, including predictive models, large language model use cases, and agentic workflows that support clinical, operational, and business objectives. Develops and maintains end-to-end machine learning and RAG pipelines supporting data ingestion, application feature engineering, training, evaluation, deployment, and lifecycle management. Architects and supports production-grade DevOps practices, including CI/CD, model versioning, automated testing, monitoring, alerting, retraining, and rollback strategies. Deploys and manages AI/ML applications in cloud environments, ensuring solutions are secure, reliable, performant, and operationally supportable. Implements observability and performance evaluation practices to manage compute resource utilization, performance, and cost efficiency. Works with AI development team to a continuous improvement feedback loop. Ensures AI/ML and agentic solutions comply with data governance, privacy, security, and responsible AI expectations, including HIPAA-aligned practices where applicable. Creates and maintains technical documentation for deployments, workflows, operational procedures, assumptions, limitations, and support processes. Troubleshoots complex pipeline, infrastructure, model, and integration issues; implements fixes and drives continuous improvement in operational stability and delivery efficiency. Core Skills: Hands-on experience with cloud-native AI/ML services and infrastructure, preferably in Google Cloud Platform (GCP), including services for training, inference, orchestration, and scalable compute Proficiency info MLOps, DevOps, and software engineering practices such as CI/CD, Git-based workflows, containerization, Infrastructure as Code, and automated testing Proficiency with establishing connections via API calls and MCP servers. Strong SQL and data engineering skills with experience in large-scale data processing, backend engineering, and integration across enterprise data platforms Experience with API development and systems integration to embed AI/ML capabilities into enterprise applications and workflows Strong analytical and problem-solving skills with the ability to diagnose issues across data, models, infrastructure, and orchestration layers Excellent communication and collaboration skills with the ability to document and explain technical concepts clearly to both technical and non-technical stakeholders Performs other duties as assigned. EDUCATION Bachelors Computer Science, Data Science, Engineering, Artificial Intelligence, Machine Learning, Mathematics, Statistics, or a related quantitative field; or 4 years’ relevant experience. Required EXPERIENCE 3 years, of progressive experience in DevOps within a Cloud deployment in AI/ML Ops, data engineering, or related software engineering roles, including at least 1 year deploying and operating AI/ML production workloads. Required LICENSE AND CERTIFICATIONS We're all in for your career. Expert care from experts who care. At HonorHealth, you’ll find something special. Our culture is built on warmth and neighborly kindness, but behind every smile is a highly skilled professional with deep expertise and unwavering dedication. We’re delivering a healthcare experience that simply feels better through: • Nine acute-care hospitals • Over 200 primary, specialty and urgent care centers • More than 17,000 team members and 4,000 medical staff Since 1927, we’ve been focused on doing what matters most — caring for people and communities across the greater Phoenix area. From humble beginnings to one of Arizona’s largest nonprofit healthcare systems, we’re just as driven as we were a century ago. Come join us and go all in for your career. 🔗 Helpful links 💼 Benefits 🖥️ Career site 🤝 Culture 📄 Hiring Process 🏥 Locations 🖥️ HonorHealth.com Join our talent community here! Stay connected with HonorHealth careers: • Get updates on hiring events • Be the first to know about new roles • Connect with our recruiters IMPORTANT: HonorHealth is committed to providing an excellent candidate experience for candidates interested in our job opportunities. We also care about the online safety of our job seekers. Please note the following: HonorHealth employee emails come from HonorHealth (i.e hr@honorhealth.com) not a generic email address, such as gmail or yahoo. If you are suspicious of a job posting, or if you receive any email from an HonorHealth employee that you believe to be fictitious, please contact us EmploymentOffice.HR@HonorHealth.com. HonorHealth does not use Google Hangouts to conduct interviews or conversations. HonorHealth will not ask you to provide any personal information (i.e. drivers license, bank account, credit card information, passwords, social security number) outside of our Applicant Tracking Software before a job offer is extended. If you believe that HonorHealth has violated your civil rights or believe you have experienced discrimination, please click the link to obtain information on your rights to file a complaint. For more information, please click here.
Posted Nov 6, 2026
