AI/Data Engineer

AI/Data Engineer
We are seeking an AI Data Integration Engineer with strong hands-on experience in Snowflake, healthcare claims data, and practical AI/LLM integration. This role will lead the creation of a sanitized claims data layer (Snowflake views, models, and pipelines) used by internal and external AI systems to identify insights, patterns, savings opportunities, and potential issues for our members and clients.

Preferred candidates will also have experience integrating AI solutions in Azure AI Foundry, enabling us to scale toward enterprise-level AI agents, copilots, and analytics capabilities in the future. This role sits at the intersection of data engineering, AI development, and healthcare domain expertise. MINIMUM REQUIREMENTS (REQUIRED TO HIRE)
Technical
? 3+ years of hands-on Snowflake experience, including: o SQL, semi-structured data (JSON), UDFs o Secure Views & Masking Policies o Data modeling (Star/Snowflake schemas) o Performance optimization
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Strong experience building ETL/ELT pipelines in a modern data stack.
? At least 1-2 years of applied AI/LLM development, including: o Designing prompt pipelines o Calling LLM APIs (Azure OpenAI, OpenAI, Anthropic, etc.) o Integrating structured data into LLM workflows
? Previous work with healthcare or claims datasets (medical or pharmacy).
? Strong understanding of HIPAA privacy principles, de-identification strategy, and PHI minimization. Soft Skills
? Clear written and verbal communication.
? Ability to translate product requirements into technical solutions.
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Comfortable working in a fast-paced, evolving environment.
? Highly collaborative; strong problem-solving mindset.

PREFERRED QUALIFICATIONS (STRONG PLUS)
Azure & Enterprise AI
? Experience with Azure AI Foundry, including: o Model catalog & deployments o Agents / tool-calling workflows o Responses API o Vector indexing and retrieval
? Experience with Azure OpenAI in a HIPAA environment.
? Familiarity with Health Data Services, FHIR, or Fabric Healthcare Data Solutions. Advanced Data & AI
? Experience building RAG pipelines, vector embeddings, semantic search.
? Experience designing AI-driven analytics, copilot-style solutions, or automated insights tools.
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Background in ML Ops, data governance, or data privacy engineering. Healthcare Domain
? PBM or payer experience (pharmacy claims, accumulators, benefit design).
? Experience generating insights such as: o Cost driver analysis o Adherence metrics o Trend & utilization insights o Plan optimization / savings recommendations
? Previous work supporting clinical, actuarial, or analytics teams.

SUCCESS CRITERIA (HOW PERFORMANCE WILL BE EVALUATED) o Snowflake sanitized views delivered, validated, and securely deployed. o AI integration produces accurate, explainable insights consistently. o Reduction in manual analysis time for internal teams. o High-quality documentation and reproducible pipelines. o Successful prototype or pilot for Azure AI Foundry-based expansion. o Trusted partnership with product, clinical, and engineering teams.

TOOLS & TECHNOLOGIES USED
Required:
Snowflake, SQL, ETL/ELT tools (DBT, Matillion, Airflow, etc.), Python, APIs, LLMs (Azure OpenAI or OpenAI), Git.

Preferred

Azure AI Foundry, Azure Functions, Azure Service Bus, Fabric, FHIR APIs, Databricks (optional), Vector DBs.