Lead Data Engineer with (Neo4j)

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.