Specialist Solutions Architect - AI/ML (Healthcare & Life Sciences)
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
About the Role
You will help Payers and Providers put generative AI to work in their business, turning complex regulated healthcare data into governed production-ready AI on Databricks. You will architect generative AI applications and agents, build data foundations, support Solution Architects in technical sales, and grow adoption through content and community engagement.
Requirements
- 5+ years hands-on experience in a technical role, with recent generative AI application or agent work
- Expertise in generative AI and agents including LLMs, RAG, agent frameworks, tool calling, MCP, fine-tuning, evaluation and guardrails
- Experience taking AI applications to production with tools like MLflow
- Strong foundation in data engineering, data warehousing or machine learning
- Production programming experience in SQL and Python, Scala or Java
- 2 years hands-on experience with big data technologies such as Spark, Hadoop and Kafka
- 2 years customer-facing pre-sales or post-sales experience
- Bachelor's degree in Computer Science, Information Systems or Engineering, or equivalent experience
- Ability to meet technical training expectations within 6 months of hire
- Ability to travel up to 30%
Responsibilities
- Guide Payer and Provider customers from AI prototype to production, architecting generative AI applications and agents with RAG, fine-tuned or open foundation models
- Build agents for workflows such as medical coding, utilization review and member and patient service, including multi-agent systems, tool calling and MCP integrations
- Apply generative AI to clinical notes, charts, call transcripts and documents
- Ground AI in governed data through context engineering, semantic layers and Genie
- Set up evaluation, tracing and monitoring for AI quality, cost and latency using MLflow
- Build data foundations including batch and streaming pipelines, data warehouses and legacy migrations
- Bring machine learning in for risk, fraud and forecasting models
- Help customers meet HIPAA and PHI requirements through Unity Catalog governance
- Support Solution Architects with proof-of-concept content, sizing estimates and custom architectures
- Grow Databricks adoption through tutorials, training, hackathons, blogs and conference presentations
Benefits
- Eligibility for annual performance bonus
- Equity