About the role
FEQ427R390
As a Specialist Solutions Architect (SSA) on the Healthcare & Life Sciences team, you will help Payers and Providers put generative AI to work at the center of their business. For Payers, that means prior authorization, claims, payment integrity, risk adjustment and the member experience. For Providers, it means clinical documentation, care management, the revenue cycle and the patient experience. Both run on complex, highly regulated data such as EHR records, claims and clinical notes. You will help them turn that data into AI on Databricks that is accurate, governed and ready for production.
In this customer-facing role, you will work with and support Solution Architects, helping customers design and implement essential workloads and shape their roadmap for expanding use of the Databricks Data Intelligence Platform. As a go-to expert reporting to the Specialist Field Engineering Manager, you will keep building your skills through mentorship, learning and internal training. You will also deepen a specialty in generative AI, AI agents, Healthcare or another area.
The impact you will have
- Guide strategic Payer and Provider customers from AI prototype to production, architecting generative AI applications and agents with retrieval-augmented generation (RAG), fine-tuned or open foundation models, and the data platforms behind them
- Build agents for Payer and Provider workflows such as medical coding, utilization review and member and patient service, including multi-agent systems, tool calling and Model Context Protocol (MCP) integrations
- Apply generative AI to clinical notes, charts, call transcripts and documents for summarization, extraction and chart review
- Ground AI in governed data through context engineering, semantic layers and natural-language analytics with Genie, so agents answer from trusted business definitions
- Set up evaluation, tracing and monitoring for AI quality, cost and latency, including LLM judges, human feedback and guardrails, using MLflow
- Build the data foundations behind AI, including batch and streaming pipelines, data warehouses and migrations from legacy platforms such as Teradata, Oracle, SQL Server, Informatica and SAS
- Bring machine learning in where it fits, such as risk, fraud and forecasting models that work alongside generative AI and agents
- Help customers work with healthcare data such as EHR, FHIR, HL7 and claims, and meet HIPAA and PHI requirements through governance with Unity Catalog
- Use AI tools, including coding assistants and agents, to move quickly from a customer problem to a working prototype and reusable solution accelerators