Knowledge Engineer

Intro: Senior Knowledge Engineer responsible for designing and operationalizing knowledge frameworks (ontologies, knowledge graphs, semantic models) that enable AI systems to reason and deliver insights. The role leads a substantial knowledge engineering scope within a large program, drives technical direction and innovation, and interfaces with business and technical stakeholders to justify and deliver graph-powered Data & AI solutions. Key responsibilities: - Lead design, development and implementation of knowledge graph and semantic solutions across a program scope. - Design and maintain ontologies, schema and semantic models; establish standards and curate KGs to ensure contextual accuracy and data quality. - Build and guide teams developing graph-based ML models, knowledge-augmented AI applications and analytic methods on knowledge graphs. - Drive end-to-end delivery: data architectures, pipelines, integration, and deployment for AI applications (including LLM-focused pipelines). - Collaborate with project leaders, delivery leads and clients; contribute to pre-sales and make the business case for semantic-layer solutions. - Provide thought leadership, publish/present perspectives, mentor junior staff and lead cross-functional teams across time zones. Required qualifications and experience: - Minimum 12 years' experience; 15 years of full-time education required; position based in Chennai office (on-site). - Bachelor's degree or equivalent; specified technical minima include: >=3 years with KG technologies (RDF, SPARQL, LPG, SHACL), >=3 years schema/ontology design and KG curation, >=3 years designing KG solutions and graph-based ML, >=2 years end-to-end data pipeline implementations for AI (esp. LLMs), >=4 years working with relational DBs, object stores, graph DBs and vector DBs, >=2 years leading a team/workstream. - Must-have: proficiency in Microsoft Azure Data Services. - Hands-on: Python and frameworks (TensorFlow, PyTorch); ETL/pipeline tools (Apache NiFi, Airflow); cloud platforms (AWS, Azure, GCP). - Practical experience with NLP and/or search techniques; prompt engineering and LLMs for enterprise-scale applications. Preferred / additional: - Team-lead and external client-facing consulting experience; broad familiarity with diverse ML techniques and agentic systems; strong collaboration and stakeholder management skills. Location & other: On-site at Accenture Chennai. Employment type: Full-time.