Director, Model Engineering & Operations

Job Summary

The Director, Model Engineering & Operations is responsible for leading the strategy, development, implementation, and optimization of enterprise AI and machine learning solutions that support core health plan operations and business objectives. This role provides leadership for the design and delivery of scalable, secure, and compliant AI/ML platforms and production systems, while overseeing the end-to-end machine learning lifecycle. The Director leads a team of machine learning engineers and applied scientists and collaborates across business and technology functions to translate advanced analytics and artificial intelligence capabilities into reliable, cost-effective, and operationalized solutions that drive organizational performance and innovation.

Essential Functions

* Lead the design, development, and productionization of ML and AI models across risk adjustment (HCC/RAF), HEDIS/Stars quality measures, care management, utilization management, fraud/waste/abuse, and member/provider experience use cases. * Own the end-to-end MLOps lifecycle on Databricks: feature engineering and feature store design, model training and versioning (MLflow), CI/CD for ML pipelines, deployment patterns (batch, real-time, and streaming inference), and automated retraining. * Establish and enforce model monitoring practices — drift detection, performance degradation alerts, bias/fairness checks, and champion-challenger frameworks — to ensure production models remain accurate and compliant over time. * Guide the evaluation and responsible adoption of generative AI and LLM-based capabilities (e.g., Mosaic AI, Genie, retrieval-augmented generation) for internal analytics, member/provider-facing tools, and operational automation. * Define engineering standards, design patterns, and reusable components (feature libraries, model templates, deployment scaffolding) to accelerate delivery across the data science and ML engineering team