• Educate and evangelize AI to boost productivity across all internal groups • Build scalable, high-availability models from claims, contracts, employer and price transparency data to create intelligence and handle real-time inference requests • Manage and optimize the underlying cloud infrastructure for both large-scale model training and high-throughput serving environments • Implement advanced monitoring and alerting systems to track model performance, data drift, and prediction latency in production • Establish processes for model versioning, lineage tracking, and rollback capabilities to ensure operational integrity and auditability • Collaborate directly with the Data Science team to containerize model code, optimize models for production serving efficiency, and transition models from research to production-readiness • Automate all aspects of the model lifecycle, from data ingestion and feature engineering to deployment and retraining triggers