Senior AI/Data Engineer (GraphRAG / Neo4j)

NDA; United States; Remote; USD 150,000 - 230,000; Full time

Job summary

NDA is building a greenfield AI-native platform to automate business processes using GraphRAG, knowledge graphs, MCP servers, and LLM orchestration. The role focuses on Python backend development, graph data modeling with Neo4j and Cosmos DB, and scalable services in FastAPI with Celery and message queues.

You will work on ML-enabled retrieval, agent technologies (LangChain/LangGraph), and cloud-native infra using Docker, Kubernetes, and CI/CD. Strong English communication is required.

Qualifications

• 5+ years of commercial Python development experience.
• Experience with graph databases (Neo4j, Azure Cosmos DB Gremlin API).
• Experience with AI/LLM systems (LangChain, LangGraph, RAG).
• Experience with MCP (Model Context Protocol) - servers and clients.
• Experience with backend development: FastAPI, Celery, PostgreSQL, Redis; experience with RabbitMQ and Kafka.

Responsibilities

• Design and implement graph data models, relationship mapping, and traversal logic using Cosmos DB (Gremlin API) and Neo4j.
• Optimize graph queries for performance at scale.
• Build GraphRAG solutions combining knowledge graphs, vector search, metadata, and LLM retrieval.
• Develop agentic AI systems with LangChain and LangGraph.
• Implement and host MCP servers/clients.
• Manage agent memory and spec-driven AI workflows.
• Integrate vector databases and semantic search platforms; develop pipelines and APIs in Python.

Skills

Python

Graph databases

Neo4j

Cosmos DB

AI/LLM

LangChain

LangGraph

MCP

FastAPI

Celery

PostgreSQL

Redis

RabbitMQ

Kafka

Docker

Kubernetes

CI/CD

English

Tools

Neo4j

Azure Cosmos DB Gremlin API

LangChain

LangGraph

MCP servers/clients

FastAPI

Celery

PostgreSQL

Redis

RabbitMQ

Kafka

Docker

Kubernetes

React

Next.js

Job description

Описание

We are helping a global leader in professional services build a next-generation AI-native platform to automate business processes. This is a greenfield project using cutting-edge technologies: GraphRAG, knowledge graphs, MCP servers, and LLM orchestration.

Задачи

• Design and implement graph data models, relationship mapping, and graph traversal logic using Azure Cosmos DB (Gremlin API) and Neo4j.
• Optimize graph queries for performance at scale;
• Build GraphRAG solutions combining knowledge graphs, vector search, metadata, and LLM-based retrieval.
• Develop agentic AI systems with LangChain and LangGraph.
• Implement and host MCP (Model Context Protocol) servers and clients.
• Manage agent memory and spec-driven AI workflows.
• Integrate vector databases and semantic search platforms;
• Develop scalable data pipelines and APIs in Python.
• Build high-performance backend services with FastAPI.
• Design event-driven architectures using Celery, RabbitMQ, and Kafka.
• Ensure code quality through testing, code reviews, and performance optimization;
• Contribute to full-stack development with React and Next.js when needed.
• Work with Docker, Kubernetes, and CI/CD pipelines.
• Support cloud-native environments and infrastructure automation.

Требования

Must-Have

• 5+ years of commercial Python development experience;
• Experience with graph databases (Neo4j, Azure Cosmos DB Gremlin API);
• Experience with AI and LLM systems (LangChain, LangGraph, RAG);
• Experience with MCP (Model Context Protocol) - servers and clients;
• Experience with backend development: FastAPI, Celery, PostgreSQL, Redis;Experience with message queues (RabbitMQ, Kafka);
• English: B2+ (Upper-Intermediate);

Nice-to-Have

• Experience with GraphRAG;
• Experience with Databricks or Delta Lake;
• Experience with Azure (Cosmos DB, AI Search);
• Experience with React or Next.js;
• Experience with Docker, Kubernetes, CI/CD;
• Experience in consulting or working with Fortune 500 clients.