AI Engineers – Ontology & Civilizational Knowledge Systems Infinity Foundation | Paid position | Part-time or full-time | Start immediately About the role: Infinity Foundation is seeking experienced AI engineers to develop an advanced, ontology-based AI knowledge system focused on Indian civilization, philosophy, history, and intellectual traditions. Infinity Foundation has an extensive repository of original civilizational knowledge, including books by Rajiv Malhotra, research papers, lectures, videos, and other scholarly materials. Our goal is to transform this vast body of knowledge into an intelligent, structured system capable of answering complex questions accurately, with reliable sources and an unbiased Indic perspective. We are looking for technically strong engineers who can combine AI, large language models (LLMs), knowledge graphs, ontologies, and advanced retrieval systems to build a scalable civilizational knowledge platform. This is a hands-on engineering position involving system architecture, development, implementation, and testing. What you will do • Design and develop ontology-based AI systems to organize and represent complex civilizational knowledge. • Build knowledge graphs that capture concepts, relationships, schools of thought (SOT), texts, thinkers, and philosophical frameworks. • Develop AI-powered question-answering systems using Infinity Foundation's existing repository of books, research, videos, and other content. • Implement LLMs, Retrieval-Augmented Generation (RAG), GraphRAG, semantic search, and related technologies. • Build pipelines to ingest, process, classify, and connect large volumes of structured and unstructured content. • Ensure answers are accurate, source-grounded, traceable, and reflect Indic knowledge traditions without ideological or cultural distortions. • Develop methods to minimize hallucinations, identify knowledge gaps, and evaluate the quality and reliability of AI-generated responses. Build and use evaluation datasets for multi-turn and adversarial tests, regression checks to assess retrieval, citation accuracy, and SOT fidelity. • Work closely with Infinity Foundation's researchers and subject experts to translate complex intellectual frameworks into computational knowledge structures. • Collaborate with IF researchers and SMEs to continually refine the system's knowledge representation and question-answering capabilities. Who we are looking for • Proven professional experience in AI/ML engineering, particularly LLM-based systems, knowledge graphs, or ontology development. • Hands-on experience building and deploying AI applications, not merely using existing AI tools. • Strong programming skills, especially Python, and experience with modern AI/ML frameworks. • Familiarity with knowledge representation technologies such as RDF, OWL, SPARQL, Neo4j, or equivalent graph technologies. • Experience with RAG architectures, vector databases, embeddings, semantic retrieval, and LLM integration. • Ability to design scalable systems that support complex reasoning and reliable question answering. • Experience working with large document collections, unstructured knowledge, or specialized domain-specific datasets. • Strong problem-solving skills and the ability to independently architect and implement technical solutions. • Interest in Indian civilization, philosophy, Sanskrit knowledge systems, or digital humanities is an advantage We are particularly interested in engineers who have successfully built knowledge-driven AI systems and can demonstrate working implementations. Terms • Paid technical engineering position; part-time or full-time arrangements available. • Remote work possible; engagements are issued in the name of Infinity Foundation. • Compensation commensurate with experience, technical expertise, and time commitment. • Position available immediately. How to apply Send a brief note describing (1) your relevant AI engineering experience; (2) projects involving ontologies, knowledge graphs, RAG, LLMs, or intelligent question-answering systems; (3) links to working projects, GitHub repositories, technical portfolios, or demonstrations of systems you have personally developed; and (4) your availability (part-time or full-time). Please include your CV and relevant technical work samples. Applicants with demonstrated experience building and deploying similar systems will be given preference. Applications will be reviewed on a rolling basis. Apply to: [email protected]