Immediate joiner AI Engineer Graph Database Specialist

About the Role

We are seeking an experienced AI Engineer with deep expertise in graph databases, particularly Neo4j, to join our team. In this role, you will design and implement AI-powered solutions that leverage graph-based data models to uncover complex relationships, enable intelligent search, and drive advanced analytics across our platform.

Responsibilities

Work closely with data scientists, software engineers, and product teams to architect and deploy AI solutions built on graph database infrastructure. Design and optimize Neo4j schemas, queries, and data pipelines to support machine learning workflows and knowledge graph applications. Develop and integrate graph-based features such as entity resolution, relationship extraction, recommendation engines, and semantic search into production systems. Build and maintain ETL processes that transform structured and unstructured data into graph representations. Collaborate on the development of retrieval-augmented generation (RAG) systems using graph databases as the knowledge layer. Evaluate and implement graph algorithms (community detection, centrality measures, pathfinding) to extract insights and enhance AI model performance. Ensure scalability, performance, and reliability of graph database deployments in cloud environments. Document technical designs, maintain code quality, and contribute to engineering best practices.

Required Qualifications

A minimum of 3 years of hands-on experience with Neo4j or similar graph databases (Amazon Neptune, TigerGraph, ArangoDB). Strong proficiency in Cypher query language and graph data modeling principles. Experience building AI/ML applications, including familiarity with frameworks such as PyTorch, TensorFlow, or scikit-learn. Solid programming skills in Python, with experience in data processing libraries (Pandas, NumPy) and API development. Understanding of knowledge graphs, ontologies, and semantic data representations. Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes). Bachelor's or Master's degree in Computer Science, Data Science, or a related field, or equivalent practical experience.

Preferred Qualifications

Experience with LLM integration, vector databases, and RAG architectures. Familiarity with graph neural networks (GNNs) and their applications. Background in healthcare, life sciences, or financial services domains. Neo4j Certified Professional certification. Experience with LangChain, LlamaIndex, or similar orchestration frameworks.

What We Offer

Competitive salary and comprehensive benefits. Opportunity to work on cutting-edge AI and graph technology. Collaborative, innovation-driven culture with room for professional growth. Flexible work arrangements.