Neo4j Lead Data Engineer

RIVAGO INFOTECH INC.
Mettawa, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Mettawa, United States of America

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Azure
Bioinformatics
Cloud Computing
Computer Programming
Information Engineering
Query Languages
Graph Database
Python
Neo4j
Node.js
Workflow Management Systems
Google Cloud Platform
Retrieval-Augmented Generation
Large Language Models
Model Validation
Generative AI
Backend
FastAPI
Information Technology
Machine Learning Operations
Virtual Agents
GPT

Job description

· 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.

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.

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