Data Engineer - AI, Agents, & Context - Clinical (Sr. Associate)
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. Our goals are: Turn structured and unstructured information into trusted, reusable "building blocks" (semantic layers, retrieval services, and agent-ready interfaces) that accelerate product innovation. Deliver transformational speed and leverage — faster time-to-insight, higher automation of knowledge work, and a foundation that scales AI safely and reliably as adoption grows. Unlock new capabilities across our business and create the foundation that drives deeper domain innovation and cross-domain collaboration. 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
- 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
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 warehouse/lakehouse 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, dental and vision coverage
- 401(k) plan with a generous employer match
- employee stock purchase plan
- generous Paid Time Off policy
- paid parental leave
- adoption assistance
- free annual health screenings and coaching
- bank at work
- on-site workshops
- ongoing programs recognizing major events in the lives of our employees throughout the year
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
