Leads the architecture, development, and productionization of AI/ML and GenAI solutions for healthcare operations. Responsibilities include building clinical and claims data pipelines, developing LLM and RAG applications, implementing MLOps and LLMOps, ensuring HIPAA-compliant governance, translating business needs into technical roadmaps, communicating with stakeholders, and mentoring engineers.

Develops and maintains ETL/ELT pipelines, legacy SSIS and SSAS solutions, reporting platforms, and relational and dimensional data models. Tunes SQL, data pipelines, semantic layers, and reporting workloads for performance and reliability. Supports Snowflake and cloud-native data platforms, documents data lineage and procedures, responds to ServiceNow incidents, and follows HIPAA, ITIL, governance, and change-control standards. Collaborates across technical and analytics teams while supporting healthcare data systems and modernization initiatives.

Lead AI/ML engineering vision and roadmap for healthcare and life sciences. Oversee multiple client engagements, design and deploy scalable production-grade AI solutions (ML, NLP, deep learning, computer vision, LLMs), ensure regulatory readiness, responsible AI practices, and drive adoption and value realization while managing executive client relationships and expanding AI adoption.