Senior AI/ML & DevOps Engineer
Company: Honorhealth
Location: Virtual Arizona (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-08-25
About this role
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 Senior AI / ML 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.
ESSENTIAL FUNCTIONS
- Leads the design and implementation of 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 pipelines spanning data ingestion, feature engineering, training, evaluation, deployment, and lifecycle management.
- Architects and supports production-grade MLOps practices, including CI/CD, model versioning, automated testing, monitoring, alerting, retraining, and rollback strategies.
- Deploys and manages AI/ML solutions in cloud environments, ensuring solutions are secure, reliable, performant, and operationally supportable.
- Implements observability and performance evaluation practices to detect drift, degradation, failures, and behavioral anomalies in models ...