Description

Key Skills: Python, Agentic AI, LLMs, Knowledge Graphs, Neo4j, LangGraph, AutoGen, LangChain, Semantic Web, GraphRAG, Cypher, RDF, OWL, SPARQL, Ontologies, AI APIs

Roles & Responsibilities:

• Design and implement agentic AI systems using frameworks such as LangGraph, AutoGen, and LangChain.
• Architect knowledge graph solutions in Neo4j to support grounding, memory, multi-hop reasoning, and explainability.
• Develop Cypher queries, graph schemas, and indexing strategies for enterprise AI workloads.
• Build and integrate semantic reasoning workflows using RDF, OWL, SPARQL, ontologies, and rule-based inference.
• Deliver scalable AI APIs and production integrations across SQL, NoSQL, vector, and graph data stores.

Experience:

• Strong hands-on experience in Python, Agentic AI, and LLM-based system design.
• Architecture experience with Knowledge Graphs and Neo4j for enterprise AI applications.
• Ability to design scalable reasoning workflows, graph schemas, and retrieval pipelines.
• Experience building production APIs and integrating AI systems with enterprise data platforms.
• 7+ years of overall experience, including 3+ years building Generative AI or Agentic AI systems in production.

Good to Have:

• Neuro-Symbolic AI, GraphRAG, and multi-agent system experience.
• Exposure to MLOps practices, CI/CD, and monitoring in AI production environments.
• Experience with regulated enterprise domains such as banking, insurance, or healthcare.

Education:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or related field

Key Skills

Education

Any Graduate