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
- Robust 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

📌 Federated Intelligence Engineer (Bengaluru)
🏢 BMW TechWorks India
📍 Bengaluru