Description

You will design and deploy end-to-end generative AI systems, including RAG pipelines and AI agents, from concept to production.

This role is on-site.

Responsibilities

• Architect GenAI solutions and GraphRAG pipelines that integrate vector databases with knowledge graphs to ground responses in factual data.
• Develop and maintain large-scale knowledge graphs using Neo4j to structure complex enterprise data.
• Build scalable data pipelines for ingestion, embedding generation, and continuous model retraining.
• Optimize open-source and proprietary LLMs by collaborating with data scientists on fine-tuning and infrastructure preparation.
• Provide technical leadership and mentorship to junior developers while defining best practices for CI/CD and testing.

Required Skills

• 7+ years of experience in software development or AI engineering with production-ready AI projects.
• Expert proficiency in Python and frameworks such as PyTorch, TensorFlow, LangChain, and LlamaIndex.
• Strong hands-on experience with graph databases, specifically Neo4j, including data modeling, Cypher, and graph algorithms.
• Deep practical knowledge of GenAI, LLMs, prompt engineering, embeddings, and RAG system architecture.
• Experience deploying and optimizing models in GCP cloud environments.
• Bachelor's or master’s degree in Computer Science, Data Science, Engineering, or a related technical field.

Preferred Skills

• Experience with MLOps and implementing responsible AI practices.

Key Skills

Education

Any Graduate