Knowledge Engineer

Overview: The Knowledge Engineer leads knowledge engineering scope within large programs to design and implement knowledge frameworks (ontologies, semantic models, knowledge graphs) that enable AI systems to reason and produce actionable insights. This is an on-site, full-time role based in Accenture’s Chennai office with a stated minimum of 12 years’ experience and 15 years of full-time education. Core responsibilities: - Lead design, development and delivery of Knowledge Graph (KG) and semantic solutions across program scope, setting standards and technical direction. - Translate expert and unstructured knowledge into ontologies, KG schemas and semantic models; curate and maintain KGs to ensure contextual accuracy and data quality. - Build and oversee graph-powered Data & AI offerings, including graph-based ML models and analytics on knowledge graphs to drive problem solving and business insights. - Design, evaluate and maintain ontologies and KG schemas; justify recommended semantic-layer solutions to stakeholders and support pre-sales and sales efforts. - Drive end-to-end delivery by collaborating with project/delivery leads and cross-functional teams; mentor and lead team members and workstreams. Required qualifications and experience (as listed): - Minimum 12 years of experience (posting text indicates a 12+ year requirement). - Educational requirement: 15 years full-time education; Bachelor's degree or equivalent is stated. - At least 3 years with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) and KG schema/ontology design and curation. - At least 3 years designing and developing KG solutions and graph-based ML models; 2+ years implementing end-to-end data pipelines for AI applications (esp. LLMs). - 4+ years with relational DBs, object stores, graph DBs (Stardog, Neo4J, Amazon Neptune) and vector DBs. - 2+ years leading a team or workstream; 2+ years with cloud platforms (AWS/Azure/GCP); 2+ years Python experience and familiarity with ML frameworks (TensorFlow, PyTorch) and ETL tools (Apache NiFi, Airflow). Preferred / Additional skills mentioned: - Practical experience with NLP and/or search techniques, prompt engineering and LLMs for enterprise-scale applications. - Client-facing consulting experience, strong collaboration across engineering, research and product teams, and thought leadership capability. A Ph.D. in Computer Science, Engineering, Mathematics or related field is also listed in the posting. Tools & technologies explicitly referenced: Microsoft Azure Data Services (must-have), Graph Databases, Stardog, Neo4J, Amazon Neptune, vector DBs, AWS, GCP, Python, TensorFlow, PyTorch, Apache NiFi, Airflow, RDF/SPARQL/SHACL, LLMs, prompt engineering, NLP/search. Location & working arrangement: - Based at Accenture Chennai office (on-site). No salary details provided in the posting.