Technical Architect
United States
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Job Description
Technical Architect
Frisco, Texas

Job Summary

We are seeking a hands-on Ontology / Knowledge Graph Engineer to design, build, and maintain enterprise knowledge models supporting network automation, semantic search, and AI/agentic use cases. The ideal candidate combines strong RDF/OWL and graph engineering skills with practical experience converting complex, real-world data into well-defined, validated semantic models.
Key Responsibilities
● Design and evolve enterprise ontologies using RDF, RDFS, OWL, Turtle (TTL), and SHACL.
● Develop class/property hierarchies, relationships, taxonomies, namespaces, constraints, and reusable ontology patterns.
● Apply both schema-first and schema-late modeling approaches, including reverse-engineering models from existing data.
● Profile and model large, complex datasets from Excel/CSV, CIQ, configuration, inventory/CMDB, JSON, and relational sources.
● Define atomic vs. derived attributes, cross-field relationships, deterministic derivation rules, and validation rules.
● Develop SPARQL 1.1 queries, competency questions, graph traversals, dependency/impact queries, and semantic validation.
● Build and maintain ontology ingestion, transformation, validation, and testing pipelines using Python.
● Work with RDF graph databases such as GraphDB/Stardog and understand Labeled Property Graph (LPG) technologies such as Neo4j.
● Support Ontology-RAG / GraphRAG / hybrid graph + vector retrieval and integration of knowledge graphs with AI agents.
● Partner with network/domain SMEs to translate implicit business and engineering knowledge into explicit, testable models.
● Maintain ontology artifacts, specifications, mappings, and validation rules in Git/CI-CD.
Required Skills & Experience
● Strong hands-on experience with RDF, RDFS, OWL, TTL, SHACL, SPARQL, and Semantic Web technologies.
● Practical knowledge of knowledge graphs, graph traversal, RDF stores, LPGs, and graph validation.
● Experience with schema-first and schema-late ontology development.
● Strong data modeling and reverse-engineering skills, including working with messy or incomplete source data.
● Experience with JSON Schema, relational data modeling, and mapping between relational/JSON and graph models.
● Strong Python skills for data processing, validation, and automation.
● Experience with graph databases such as GraphDB, Stardog, Neo4j, or similar.
● Experience with Git and CI/CD development practices.
Preferred Qualifications
● Master’s or PhD in Data Science, Computer Science, Artificial Intelligence, Knowledge Representation, Information Science, Engineering, or a related technical field preferred.
● Telecom / 5G & 4G network domain knowledge, including network functions, transport, inventory, configuration, and network relationships.
● Experience with Kubernetes and Helm configuration data.
● Experience with Ontology-RAG (O-RAG), GraphRAG, RAG, vector databases, and AI agent integration.
● Familiarity with MCP and agentic AI architectures.
● Experience with ontology design patterns such as SKOS and PROV-O.
● Familiarity with AI-assisted engineering tools such as Claude Code

Key Responsibilities

Design and evolve enterprise ontologies using RDF, RDFS, OWL, Turtle (TTL), and SHACL.
● Develop class/property hierarchies, relationships, taxonomies, namespaces, constraints, and reusable ontology patterns.
● Apply both schema-first and schema-late modeling approaches, including reverse-engineering models from existing data.
● Profile and model large, complex datasets from Excel/CSV, CIQ, configuration, inventory/CMDB, JSON, and relational sources.
● Define atomic vs. derived attributes, cross-field relationships, deterministic derivation rules, and validation rules.
● Develop SPARQL 1.1 queries, competency questions, graph traversals, dependency/impact queries, and semantic validation.
● Build and maintain ontology ingestion, transformation, validation, and testing pipelines using Python.
● Work with RDF graph databases such as GraphDB/Stardog and understand Labeled Property Graph (LPG) technologies such as Neo4j.
● Support Ontology-RAG / GraphRAG / hybrid graph + vector retrieval and integration of knowledge graphs with AI agents.
● Partner with network/domain SMEs to translate implicit business and engineering knowledge into explicit, testable models.
● Maintain ontology artifacts, specifications, mappings, and validation rules in Git/CI-CD.

Skill Requirements

Strong hands-on experience with RDF, RDFS, OWL, TTL, SHACL, SPARQL, and Semantic Web technologies.
● Practical knowledge of knowledge graphs, graph traversal, RDF stores, LPGs, and graph validation.
● Experience with schema-first and schema-late ontology development.
● Strong data modeling and reverse-engineering skills, including working with messy or incomplete source data.
● Experience with JSON Schema, relational data modeling, and mapping between relational/JSON and graph models.
● Strong Python skills for data processing, validation, and automation.
● Experience with graph databases such as GraphDB, Stardog, Neo4j, or similar.
● Experience with Git and CI/CD development practices.

Other Requirements

Master’s or PhD in Data Science, Computer Science, Artificial Intelligence, Knowledge Representation, Information Science, Engineering, or a related technical field preferred.
● Telecom / 5G & 4G network domain knowledge, including network functions, transport, inventory, configuration, and network relationships.
● Experience with Kubernetes and Helm configuration data.
● Experience with Ontology-RAG (O-RAG), GraphRAG, RAG, vector databases, and AI agent integration.
● Familiarity with MCP and agentic AI architectures.
● Experience with ontology design patterns such as SKOS and PROV-O.
● Familiarity with AI-assisted engineering tools such as Claude Code
Maximum Salary (US): 
Minimum Salary (US): 
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Information at a Glance

Why HCLTech?

At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first.

HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion. 

 

Compensation and Benefits

A candidate’s pay within the range will depend on their skills, experience, education, and other factors permitted by law. This role may also be eligible for performance-based bonuses subject to company policies. In addition, this role is eligible for the following benefits subject to company policies: medical, dental, vision, pharmacy, life, accidental death & dismemberment, and disability insurance; employee assistance program; 401(k) retirement plan; 10 days of paid time off per year (some positions are eligible for need-based leave with no designated number of leave days per year); and 10 paid holidays per year.