Senior AI Engineer – Knowledge Graph & Agentic Systems

This full-time, on-site role in Hyderabad focuses on building production-grade knowledge graph and agentic AI systems with LLM and GraphRAG frameworks. The engineer works with enterprise clients, architects and technical teams to design and deploy AI solutions.

Responsibilities

• Design knowledge graphs with Neo4j, Amazon Neptune or TigerGraph, and develop GraphRAG and ontology-based systems.
• Build multi-agent systems with LangGraph, LangChain and CrewAI, and develop LLM-powered applications using OpenAI, Claude, Llama, Gemini or Bedrock.
• Write production-grade Python backend services and APIs; optimize retrieval, reasoning and AI workflows; and contribute to CI/CD, testing, observability and deployment.

Required qualifications

• 8–12 years of software engineering experience and 3+ years of AI/ML engineering experience. A separate listing on the page gives 8–14 years of experience.
• Strong Python; knowledge graphs, GraphRAG or RAG, agent frameworks, vector databases such as Pinecone, Weaviate, Qdrant or FAISS, and LLM integration and deployment.
• Experience with AWS, Azure or GCP, Docker and CI/CD.

Preferred qualifications include Cypher, Gremlin or SPARQL; ontology and schema design; multi-agent systems; AWS Bedrock, SageMaker, Lambda or IAM; SAP or ERP data exposure; and research or open-source contributions. Graph theory, semantic search and knowledge representation are listed as nice to have.