Senior AI Context Engineer - RAG & Semantic Retrieval

GEHA Health; Missouri; Hybrid; USD 124,666 - 157,710; Full time

Benefits offered by this job

Competitive pay

Incentive plan

Health/Dental/Vision benefits

401(k) match

PTO & wellness programs

Job summary

G.E.H.A Health seeks a Senior AI Context Engineer within Digital Innovation to transform diverse policy, clinical, and enterprise data into accurate contextual assets for AI workflows. You will own extraction, chunking, vector indexing, and RAG retrieval to power enterprise AI tools.

Collaborate with AI architects and developers to ensure secure, compliant access to PHI and robust context provisioning for generative AI applications across the organization.

Qualifications

• 5+ years of experience in backend software engineering, applied ML/search, or data-centric app development.
• 1–2 years of hands-on GenAI and RAG optimization for LLMs.
• Proficiency in Python and SQL; familiarity with orchestration tools (Airflow, Prefect, Temporal).
• Experience with unstructured data parsing (PDFs, documents) and vector stores (Pinecone, pgvector).
• Healthcare data handling and HIPAA/HITRUST awareness.

Responsibilities

• Design and refine context extraction, chunking, and semantic search for high-quality LLM prompts.
• Implement vector indexing and retrieval pipelines with accurate metadata tagging.
• Ensure security, compliance, and RBAC for contextual data access in HIPAA environments.
• Collaborate with Sr. AI Solutions Architect and AI Full Stack Developers to deliver context layers for GenAI features.
• Develop evaluation frameworks to measure retrieval recall, precision, and groundedness.

Skills

Backend development

Applied ML/AI

Data-centric development

Python

SQL

Airflow

Prefect

Temporal

Vector retrieval

HIPAA compliance

RBAC

Tools

Pinecone

pgvector

Weaviate

Qdrant

Azure AI Search

LlamaIndex

Unstructured.io

LangChain

Job description

G.E.H.A Health seeks a Senior AI Context Engineer within Digital Innovation to transform diverse policy, clinical, and enterprise data into accurate contextual assets for AI workflows. You will own extraction, chunking, vector indexing, and RAG retrieval to power enterprise AI tools.

Collaborate with AI architects and developers to ensure secure, compliant access to PHI and robust context provisioning for generative AI applications across the organization.