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Tier-1 employer, mid-level (5+ yrs), and metro Hyderabad increase candidate competition.
Specialized graph, ontology, and TIMBR-like skills create strong domain bias, limiting cross-industry transferability.
Explicit 5+ years, mandatory graph/AWS/TIMBR skills and semantic expertise imply high strictness.
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Design, build, and maintain graph-based data structures and knowledge graph solutions using AWS and TIMBR-like platforms to power enterprise context services and AI/agentic applications.
Model consistent semantic structures representing enterprise context and ensure graph data pipelines ingest, transform, and populate data reliably from source systems.
Optimize graph performance, support validation, versioning, lineage, operational monitoring, and expose graph data via APIs to downstream applications and AI workflows.
5+ years of experience in data, graph, or semantic engineering roles.
Strong hands-on experience with AWS cloud technologies and TIMBR or similar ontology-driven platforms.
Experience with graph databases, knowledge graphs, semantic data modeling, and production-ready data pipeline development.
Familiarity with agentic AI concepts including prompt and context engineering.
Experienced in graph modeling and semantic technologies with a focus on scalable, enterprise-grade knowledge graph infrastructure.
Comfortable working in collaborative environments with architects, ontology modelers, data engineers, and platform teams to align graph solutions with enterprise standards.
Skilled at optimizing graph systems to enable reliable, governed, and interoperable context services used by AI and enterprise applications.