Senior AI/ML Engineer- Python, Databricks, LLM, Azure

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. The AAV team owns Apollo, Optum South's governed data spine, and Horizon Compass, its unified provider-facing dashboard platform. We're building AI-powered analytics and agentic tools directly on top of Apollo/Databricks - role-based provider agents, clinical intelligence summarization, and AI-assisted decision support across HEDIS quality, risk, affordability, and care management domains. We're looking for a Senior AI/ML Engineer to help design, build, and productionize the next generation of these systems - someone who can move from architecture to shipped agent in a governed healthcare data environment.

Design and build LLM-based agents and AI/ML pipelines on Databricks, extending our existing role-based agent architecture (Provider 360, Patient 360, Clinic 360 surfaces) Build and maintain RAG systems - retrieval design, grounding, and hallucination mitigation - against Apollo's governed Gold-layer data Apply and extend Databricks AI functions ( ai_summarize() , ai_classify() ) across clinical intelligence domains (HEDIS, admits/readmits, care & value) Own model evaluation and prompt versioning practices - systematic testing, not ad hoc iteration Deploy and monitor models in production on Azure, with CI/CD covering model, data, and prompt versioning together Partner with the AI Review Board (AIRB) on governance - surface risk early, support pilot-first rollout strategies Translate technical tradeoffs for non-technical and executive stakeholders, including direct exposure to CIO-level presentations Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Graduate degree or equivalent experience Core technical Hands-on experience building and shipping LLM-based agents (multi-tool orchestration, not just API calls) RAG and vector search experience - chunking strategy, retrieval design, grounding Proven solid production-grade Python and SQL Databricks fluency: Delta Lake, Unity Catalog, Genie spaces, AI functions Prompt engineering and LLM evaluation - systematic testing/versioning discipline MLOps / production Cloud model deployment and monitoring experience (Azure preferred) Experience building on governed data pipelines (Gold-layer/data-product design) CI/CD for ML pipelines, including data and prompt versioning Judgment Proven to explain model behavior and tradeoffs to non-technical and executive stakeholders Governance-minded - Proven proactive about surfacing risk before deployment Preferred Qualifications: Snowflake experience alongside Databricks LangChain or comparable agent framework experience Healthcare/HEDIS or claims data domain knowledge Exposure to ADT/change-data-capture pipelines Why This Role You'd be joining at a pivotal point - Apollo is expanding beyond Optum South, with Optum West, East, and Mid-East regions actively engaging to adopt what