Senior AI Engineer with Graph (GraphRAG, Neo4J)

We are looking for a
Senior AI Engineer with Data engineering experience
for the team of our Fortune 50 client, building scalable, production-grade data and AI-enabled systems. The main objective of the role is to design and develop scalable data pipelines, backend services, and APIs, as well as build knowledge graph solutions, including graph data modeling, relationship mapping, and graph traversal logic.

This is a
long-term remote-first contract position
with a required overlap of
US working hours (2-6 PM CET)
.

Responsibilities

• Build ETL pipelines
• Design data models.
• Design and implement GraphRAG solutions combining knowledge graphs, vector search, metadata, and LLM-based retrieval.
• Create Source to Target Mappings (STMs) for ETL specifications.
• Implement automated ingestion patterns, incremental (delta) updates, and streaming/CDC workflows.

Collaboration & Agile Development

• Gather requirements , set targets , define interface specifications , and conduct design sessions .
• Work closely with data consumers to ensure proper integration.
• Adapt and learn in a fast-paced project environment.

Work Conditions

• Type: Full-time & Long-term contract work
• Start Date: ASAP
• Location: Remote (99%) in Europe; must be able to travel freely within Europe for workshops.
• US Time Zone Overlap : Required ( 2 PM - 6 PM CET )
• Contract with European LLC
• Rate: 300-340 EUR/day

Job Requirements

• Strong proficiency in Python, building backend services/APIs as well as data pipelines
• ETL, data modeling, and performance tuning experience
• Experience with Neo4j, Cosmos DB or Gremlin API.
• Knowledge of GraphRAG, retrieval systems, LLMs, embeddings and RAG pipelines.
• Hands-on GenAI experience: LangGraph (or similar), MCP, RAG, agentic memory management and other concepts
• Hands-on data experience with Microsoft Fabric, Synapse, ADF, or similar cloud data stacks.
• Understanding of software engineering and testing practices within an Agile environment .
• Experience with Data as Code; version control, small and regular commits, unit tests, CI/CD, packaging, familiarity with containerization tools such as Docker (must have) and Kubernetes (plus).
• Excellent teamwork and communication skills.
• Proficiency in English, with strong written and verbal communication skills.
• Efficient, high-performance data pipelines for real-time and batch data processing.

Nice to have:

• Experience with Databricks or similar data platforms.
• Vector databases, Azure AI Search, or semantic search platforms.