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Lead Data Engineer with (Neo4j)

Job

Rivago infotech inc

Lake Forest, IL (In Person)

Full-Time

Posted 4 days ago (Updated 1 day ago) • Actively hiring

Expires 7/8/2026

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Job Description

Role:
Neo4j
Lead Data Engineer Location:
Mattawa, IL (Onsite)
Duration:
Long term
Project Role Overview:
We are seeking an innovative Neo4j Lead to spearhead the design and deployment of Knowledge Graph-driven AI systems. You will build intelligent, autonomous, multi-agent frameworks that streamline complex pharmaceutical market access, formulary analysis, pricing strategies, and patient journey mapping. Key Responsibilities •
Graph Architecture & Engineering:
Architect, design, and scale Neo4j graph databases (and Knowledge Graphs) representing complex biomedical, formulary, and payer datasets. •
Agentic AI Orchestration:
Build autonomous AI agents using frameworks like LangGraph or CrewAI to automate market access queries, policy analysis, and competitive intelligence reporting. • Generative
AI & RAG
: Develop Graph-RAG (Retrieval-Augmented Generation) pipelines to ensure AI models generate highly accurate, compliant, and explainable insights regarding global drug pricing and market access. •
Domain Leadership:
Translate domain-specific pharma challenges (e.g., pricing, reimbursement, HEOR data, and payer policies) into actionable technical specifications. •
Model Evaluation & MLOps :
Implement LLMOps to continuously evaluate, monitor, and refine the reasoning and tool-calling capabilities of deployed AI agents. Core Technical Requirements •
Graph Databases:
Expert-level proficiency in Neo4j, Cypher query language, and graph data modeling. •
GenAI & Agents:
Hands-on experience with LLMs (GPT, Claude), vector databases (Pinecone, Weaviate), and agentic orchestration tools (LangChain, LangGraph, or AutoGen). •
Programming:
Strong backend development skills in Python (FastAPI) or Node.js. •
Cloud Infrastructure:
Experience deploying AI and graph solutions on AWS, Google Cloud Platform, or Azure. •
Domain Knowledge:
Deep understanding of the Pharmaceutical Market Access ecosystem (P&T Committees, formulary data, value dossiers, and HEOR). Qualifications & Experience •
Education:
B.S. or M.S. in Computer Science, Data Science, Bioinformatics, or a related field. •
Experience:
8+ years in software/data engineering with at least 3+ years directly leading graph database projects and 2+ years building production-grade GenAI/Agentic AI systems. •
Pharma Experience:
Proven track record of delivering compliant, audit-ready AI solutions within the Life Sciences or Pharmaceutical industry.