Data Engineer - AI, Agents, & Context - Revenue Cycle (Associate)

Huron • Chicago, IL

2d • Remote

About The Position

This role sits within a strategic investment to embed AI into how we operate, serve customers, and make decisions within our healthcare business. We're building a healthcare-wide AI data and context platform with a focus on deep domain expertise embedded throughout our architecture. This is a hands-on technical contributor who builds and maintains core AI/context data capabilities. The role executes key parts of the AI context platform — unstructured ingestion, embeddings, retrieval, and semantic layers — working closely with senior engineers and cross-functional partners to ship reliable, production-grade AI data products.

Requirements

• 3–6 years in data engineering or data platform roles with strong hands-on delivery
• Strong SQL and Python (or Scala/Java); solid production engineering habits
• Hands-on experience with Snowflake, including pipeline design, data modeling, and operating at scale in a production environment
• Experience designing and operating cloud data pipelines at scale
• Experience working with unstructured data processing and search/retrieval concepts
• Clear communicator who can work effectively across technical and functional teams

Nice To Haves

• Hands-on experience with vector search and embeddings (pgvector/Pinecone/Weaviate/OpenSearch/Elastic) and retrieval patterns (semantic retrieval, hybrid search, reranking)
• Experience supporting LLM applications (RAG, agent tool interfaces, evaluation/observability)
• Familiarity with knowledge graphs, semantic modeling, or metrics layers
• Experience in regulated environments and data governance programs
• Exposure to dbt, Iceberg, or other lakehouse/semantic layer tooling alongside Snowflake

Responsibilities

• Build and contribute to the AI context platform
• Implement end-to-end pipelines: ingestion → parsing/chunking → enrichment → embeddings → vector indexing → retrieval/serving
• Build and maintain patterns for incremental refresh, backfills, re-embeddings, deduplication, and lineage across unstructured sources
• Contribute to retrieval quality improvements (query strategies, hybrid search, metadata filtering) in partnership with AI engineers
• Deliver semantic and governed data products
• Implement semantic layers (metrics/entities) that power BI and agent reasoning consistently
• Apply established data contracts and context contracts for AI inputs (schemas, metadata requirements, freshness, citation expectations)
• Ensure datasets and indexes are documented and reusable
• Support reliability and performance across assigned workstreams: monitoring, alerting, runbooks, and incident response
• Contribute to cost and latency optimization across Snowflake and vector infrastructure
• Apply security-by-design patterns: RBAC/ABAC, PII redaction, retention controls, and audit logging
• Follow established guardrails for AI access to enterprise knowledge in coordination with Security/Legal/Compliance

Benefits

• medical coverage
• dental coverage
• vision coverage
• 401(k) plan with a generous employer match
• employee stock purchase plan
• generous Paid Time Off policy
• paid parental leave
• adoption assistance
• Wellness Program supports employee total well-being by providing free annual health screenings and coaching, bank at work, and on-site workshops, as well as ongoing programs recognizing major events in the lives of our employees throughout the year.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed