Senior Data Engineer – AI / ML (Databricks & Azure)

We are looking for a hands-on senior engineer to support a clinical analytics and health economics team working at EMR level data depth. This is an execution first, highly technical role focused on integrating AI and LLM capabilities into an existing Databricks on Azure environment within enterprise security constraints. This is not a strategy or advisory role. The expectation is to build, integrate, and operationalize solutions in close partnership with clinical and health economics stakeholders. Key responsibilities • Work directly within Databricks on Azure to develop and maintain data pipelines • Integrate LLM and RAG based workflows into Databricks without moving sensitive clinical data • Build secure APIs and orchestration layers connecting AI components to analytics workflows • Support fine tuning and deployment of enterprise safe LLMs behind the firewall • Implement governance, logging, explainability, and audit support for AI workflows • Partner closely with clinical analytics and health economics teams to operationalize models • Navigate enterprise security, privacy, and compliance reviews and approvals • Hand off clean, well-documented solutions to internal teams for ongoing use Required experience • Strong hands-on experience with Databricks in production environments • Deep familiarity with Azure services supporting analytics and AI • Experience integrating LLMs and RAG pipelines in enterprise, security restricted environments • Solid Python experience for data engineering and AI workflows • Experience working with large scale clinical or healthcare datasets (EMR preferred) • Comfort building APIs and integration layers • Experience operating within strict security, privacy, and compliance guardrails Nice to have • Experience in healthcare analytics, population health, or clinical data • Familiarity with Markov models or disease progression analytics • Prior work supporting value-based care or health economics teams • Exposure to low code or copilot style AI tooling What success looks like • AI and LLM workflows running cleanly inside Databricks • Security approvals cleared once and reused across multiple use cases • Internal teams able to extend and operate what is built • Follow on use cases emerging without heavy rework Why this role matters This role sits at the intersection of clinical insight and AI execution. The work directly supports better care delivery, earlier intervention, and more sustainable value-based outcomes in a real-world healthcare environment.