Federated Intelligence Engineer - AIML

Required Experience, minimum: 7 years

Required Experience, maximum: 9 years

• Skills: AI Tools, ML frameworks, Pytorch

• Minimum Qualification: M Tech

We are looking for a Federated Intelligence Engineer to build intelligent systems that bring together distributed knowledge, semantic reasoning, hybrid retrieval, and LLM\-based agents.

The role focuses on creating solutions where Knowledge Graphs, GraphRAG, vector retrieval, ontologies, reasoning engines, and Agentic AI work together to provide accurate, explainable, and efficient answers.

### **Key Responsibilities**

• Design and implement GraphRAG and hybrid retrieval solutions combining vector search with graph\-based retrieval and expansion.
• Build and maintain knowledge graphs and ontologies using RDF, OWL, and SPARQL.
• Model complex domain relationships, including causal and cause\-effect relationships.
• Implement semantic reasoning using technologies such as RDFox and/or SemReasoner.
• Combine knowledge\-graph retrieval with embeddings and vector databases such as ChromaDB.
• Develop GenAI backend components and services using TypeScript and Node.js.
• Build LLM agent tools and MCP servers that enable models to interact reliably with enterprise knowledge and services.
• Design effective tool descriptions, interfaces, and context that guide LLM tool selection and behavior.
• Benchmark and continuously improve answer quality, retrieval accuracy, reasoning effectiveness, and token consumption.
• Troubleshoot issues across the complete retrieval and reasoning pipeline and address root causes rather than symptoms.
• Support containerized and multi\-service development environments.

### **Must\-Have Skills**

• Hands\-on experience with GraphRAG and/or hybrid retrieval
• Vector search combined with Knowledge Graph traversal/expansion
• Strong understanding of Knowledge Graphs and semantic technologies
• Strong knowledge of RDF, OWL, and SPARQL
• Experience with RDFox, SemReasoner, or similar reasoning\-capable triple stores
• Hands\-on experience in ontology modelling
• Experience modelling causal/cause\-effect relationships
• Practical experience with embeddings and vector databases, preferably ChromaDB
• Strong TypeScript and Node.js development skills
• Experience developing LLM agent tools
• Experience with or strong exposure to Model Context Protocol (MCP) servers
• Strong engineering mindset around evaluation, benchmarking, answer quality, and token\-cost optimization
• Strong problem\-solving mindset with emphasis on root\-cause analysis

### **Nice\-to\-Have Skills**

• Reasoning\-based validation
• Time\-series and signal analysis
• Cross\-correlation and anomaly detection
• Docker
• Shell scripting
• Multi\-service/containerized development environments