Data Engineer - AI, Agents, & Context - Clinical (Sr. Associate)
Huron helps its clients drive growth, enhance performance and sustain leadership in the markets they serve. We help healthcare organizations build innovation capabilities and accelerate key growth initiatives, enabling organizations to own the future, instead of being disrupted by it. Together, we empower clients to create sustainable growth, optimize internal processes and deliver better consumer outcomes.
Health systems, hospitals and medical clinics are under immense pressure to improve clinical outcomes and reduce the cost of providing patient care. Investing in new partnerships, clinical services and technology is not enough to create meaningful and substantive change. To succeed long-term, healthcare organizations must empower leaders, clinicians, employees, affiliates and communities to build cultures that foster innovation to achieve the best outcomes for patients.
Joining the Huron team means you’ll help our clients evolve and adapt to the rapidly changing healthcare environment and optimize existing business operations, improve clinical outcomes, create a more consumer-centric healthcare experience, and drive physician, patient and employee engagement across the enterprise.
Join our team as the expert you are now and create your future.
Role Summary
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.
Key Responsibilities
Build and contribute to the AI context platform
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Implement end-to-end pipelines: ingestion → parsing/chunking → enrichment → embeddings → vector indexing → retrieval/serving
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Build andmaintainpatterns for incremental refresh, backfills, re-embeddings, deduplication, and lineage across unstructured sources
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Contribute to retrieval quality improvements (query strategies, hybrid search, metadata filtering) in partnership with AI engineers
Deliver semantic and governed data products
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Implement semantic layers (metrics/entities) that power BI and agent reasoning consistently
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Apply established data contracts and context contracts for AI inputs (schemas, metadata requirements, freshness, citation expectations)
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Ensure datasets and indexes are documented and reusable
Operational excellence
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Support reliability and performance across assigned workstreams: monitoring, alerting, runbooks, and incident response
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Contribute to cost and latency optimization across warehouse/lakehouseand vector infrastructure
AI safety and compliance
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Apply security-by-design patterns: RBAC/ABAC, PII redaction, retention controls, and audit logging
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Follow established guardrails for AI access to enterprise knowledge in coordination with Security/Legal/Compliance
Travel Expectations
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Ability to travel as needed up to 4 times per year.
Required Qualifications
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BA or BS required, preferably in Computer Science, Engineering, or a technology-based discipline
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3–6 years in data