Specialist Solutions Architect - AI/ML (Healthcare & Life Sciences)

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
• Support Solution Architects on the advanced parts of the technical sale, including custom proof-of-concept content, workload sizing estimates and custom architectures
• Grow adoption of Databricks with customers and the broader community through tutorials, training, hackathons, blogs and Healthcare conference presentations

What we look for

• 5+ years of hands-on experience in a technical role, with recent hands-on work building generative AI applications or agents
• Expertise in generative AI and agents, including LLMs, RAG, agent frameworks, tool calling and MCP, prompt and context engineering, fine-tuning, evaluation and guardrails
• Experience taking AI applications or agents to production to solve business problems, including tracing, evaluation, monitoring, serving and cost control, with tools like MLflow
• A strong foundation in data engineering, data warehousing or machine learning, such as pipelines and streaming, data modeling and SQL performance, warehouse migrations, model development and MLOps
• Experience maintaining and extending production data systems as needs grow more complex
• Comfort using AI coding assistants and agents in day-to-day development and prototyping
• Production programming experience in SQL and Python, Scala or Java
• 2 years of hands-on professional experience with big data technologies (such as Spark, Hadoop and Kafka) and architectures
• 2 years of customer-facing experience in a pre-sales or post-sales role
• Bachelor’s degree in Computer Science, Information Systems or Engineering, or equivalent work experience
• Ability to meet technical training and role-specific expectations within 6 months of hire
• Ability to travel up to 30% when needed

Preferred qualifications:

• Education in a healthcare-related field (for example health informatics, biostatistics, epidemiology, public health or health economics), or equivalent experience
• Experience with Payers or Providers, such as claims, care management, risk adjustment, quality measures, clinical operations, EHR data or revenue cycle management