Description

You will architect and implement end-to-end GenAI solutions, including RAG pipelines and AI agents, from concept to production.

This role is on-site.

Responsibilities

• Design and maintain large-scale knowledge graphs using Neo4j to structure complex enterprise data.
• Build GraphRAG pipelines that integrate vector databases and knowledge graphs to ground AI responses.
• Set up scalable data pipelines for ingestion, embedding generation, and continuous model training.
• Collaborate with data scientists and ML engineers to prepare infrastructure for LLM fine-tuning and optimization.
• Partner with cross-functional teams to translate business needs into scalable AI architectures.

Required Skills

• 7+ years of experience in software development or AI engineering with production-ready AI projects.
• Expert-level proficiency in Python and AI/ML frameworks such as PyTorch, TensorFlow, LangChain, and LlamaIndex.
• Strong hands-on experience with Neo4j, including data modeling, Cypher, and graph algorithms.
• Deep understanding of GenAI concepts, LLMs, prompt engineering, and RAG system construction.
• Experience deploying and optimizing models in Google Cloud Platform (GCP).
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.

Key Skills

Education

Bachelor's or Master's degrees