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Strong Tier-1 brand and metro location increase applicant density despite niche semantic knowledge requirements.
Specialized knowledge-graph, RDF/OWL, and agentic AI focus reduces cross-industry transferability.
Mandatory 7+ years and specialized knowledge-graph and semantic tech requirements make screening stringent.
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Own the technical design and implementation of scalable data pipelines to ingest, transform, validate, and publish enterprise context into a knowledge graph and semantic layer.
Establish and enforce technical standards for context data contracts, transformation logic, monitoring, and operational readiness including batch and near-real-time support.
Collaborate with ontology, architecture, data engineering, and platform teams to ensure semantic standards and enable agentic AI capabilities through reliable, governed context pipelines.
7+ years of experience in data engineering, pipeline engineering, or technical architecture roles.
Strong hands-on experience with scalable data pipelines, knowledge graphs, ontologies, RDF, OWL, semantic enrichment, and entity modeling.
Working knowledge of agentic AI, prompt engineering, and context engineering concepts.
No relocation or visa sponsorship; based in Hyderabad as per JD location; Travel Requirements: No travel required.
Experienced technical leader with deep expertise in data and semantic pipeline architecture for knowledge graph population in enterprise environments.
Skilled in integrating semantic standards with data engineering to support AI-driven context and interoperability across systems.
Comfortable working cross-functionally with ontology experts, architects, and platform teams to deliver production-grade, monitored context services for AI and application consumption.