{"id":2929460,"url":"https://alion.io/job/hcltech-technical-architect-55","title":"Technical Architect","company":{"id":225,"name":"HCLTech","domain":"hcltech.com","url":"https://alion.io/company/hcltech","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"staff","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Frisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":143000,"max_usd":266000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1432},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Git","optional":false},{"name":"GraphDB","optional":false},{"name":"GraphRAG","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Neo4j","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Claude Code","optional":true},{"name":"Helm","optional":true},{"name":"Kubernetes","optional":true},{"name":"Model Context Protocol","optional":true}],"status":"live","first_seen_at":"2026-10-20T14:17:11Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-22T10:45:43Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Job Summary\nWe 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.\nKey Responsibilities\nDesign and evolve enterprise ontologies using RDF, RDFS, OWL, Turtle (TTL), and SHACL.\nDevelop class/property hierarchies, relationships, taxonomies, namespaces, constraints, and reusable ontology patterns.\nApply both schema-first and schema-late modeling approaches, including reverse-engineering models from existing data.\nProfile and model large, complex datasets from Excel/CSV, CIQ, configuration, inventory/CMDB, JSON, and relational sources.\nDefine atomic vs. derived attributes, cross-field relationships, deterministic derivation rules, and validation rules.\nDevelop SPARQL 1.1 queries, competency questions, graph traversals, dependency/impact queries, and semantic validation.\nBuild and maintain ontology ingestion, transformation, validation, and testing pipelines using Python.\nWork with RDF graph databases such as GraphDB/Stardog and understand Labeled Property Graph (LPG) technologies such as Neo4j.\nSupport Ontology-RAG / GraphRAG / hybrid graph + vector retrieval and integration of knowledge graphs with AI agents.\nPartner with network/domain SMEs to translate implicit business and engineering knowledge into explicit, testable models.\nMaintain ontology artifacts, specifications, mappings, and validation rules in Git/CI-CD.\nRequired Skills & Experience\nStrong hands-on experience with RDF, RDFS, OWL, TTL, SHACL, SPARQL, and Semantic Web technologies.\nPractical knowledge of knowledge graphs, graph traversal, RDF stores, LPGs, and graph validation.\nExperience with schema-first and schema-late ontology development.\nStrong data modeling and reverse-engineering skills, including working with messy or incomplete source data.\nExperience with JSON Schema, relational data modeling, and mapping between relational/JSON and graph models.\nStrong Python skills for data processing, validation, and automation.\nExperience with graph databases such as GraphDB, Stardog, Neo4j, or similar.\nExperience with Git and CI/CD development practices.\nPreferred Qualifications\nMaster’s or PhD in Data Science, Computer Science, Artificial Intelligence, Knowledge Representation, Information Science, Engineering, or a related technical field preferred.\nTelecom / 5G & 4G network domain knowledge, including network functions, transport, inventory, configuration, and network relationships.\nExperience with Kubernetes and Helm configuration data.\nExperience with Ontology-RAG (O-RAG), GraphRAG, RAG, vector databases, and AI agent integration.\nFamiliarity with MCP and agentic AI architectures.\nExperience with ontology design patterns such as SKOS and PROV-O.\nFamiliarity with AI-assisted engineering tools such as Claude Code\nKey Responsibilities\nDesign and evolve enterprise ontologies using RDF, RDFS, OWL, Turtle (TTL), and SHACL.\nDevelop class/property hierarchies, relationships, taxonomies, namespaces, constraints, and reusable ontology patterns.\nApply both schema-first and schema-late modeling approaches, including reverse-engineering models from existing data.\nProfile and model large, complex datasets from Excel/CSV, CIQ, configuration, inventory/CMDB, JSON, and relational sources.\nDefine atomic vs. derived attributes, cross-field relationships, deterministic derivation rules, and validation rules.\nDevelop SPARQL 1.1 queries, competency questions, graph traversals, dependency/impact queries, and semantic validation.\nBuild and maintain ontology ingestion, transformation, validation, and testing pipelines using Python.\nWork with RDF graph databases such as GraphDB/Stardog and understand Labeled Property Graph (LPG) technologies such as Neo4j.\nSupport Ontology-RAG / GraphRAG / hybrid graph + vector retrieval and integration of knowledge graphs with AI agents.\nPartner with network/domain SMEs to translate implicit business and engineering knowledge into explicit, testable models.\nMaintain ontology artifacts, specifications, mappings, and validation rules in Git/CI-CD.\nSkill Requirements\nStrong hands-on experience with RDF, RDFS, OWL, TTL, SHACL, SPARQL, and Semantic Web technologies.\nPractical knowledge of knowledge graphs, graph traversal, RDF stores, LPGs, and graph validation.\nExperience with schema-first and schema-late ontology development.\nStrong data modeling and reverse-engineering skills, including working with messy or incomplete source data.\nExperience with JSON Schema, relational data modeling, and mapping between relational/JSON and graph models.\nStrong Python skills for data processing, validation, and automation.\nExperience with graph databases such as GraphDB, Stardog, Neo4j, or similar.\nExperience with Git and CI/CD development practices.\nOther Requirements\nMaster’s or PhD in Data Science, Computer Science, Artificial Intelligence, Knowledge Representation, Information Science, Engineering, or a related technical field preferred.\nTelecom / 5G & 4G network domain knowledge, including network functions, transport, inventory, configuration, and network relationships.\nExperience with Kubernetes and Helm configuration data.\nExperience with Ontology-RAG (O-RAG), GraphRAG, RAG, vector databases, and AI agent integration.\nFamiliarity with MCP and agentic AI architectures.\nExperience with ontology design patterns such as SKOS and PROV-O.\nFamiliarity with AI-assisted engineering tools such as Claude Code","description_format":"text","description_chars":5679,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated Teams","Systems Integrators"],"lifecycle":[{"event":"open","at":"2026-10-20T14:17:11Z"}],"visa":[],"liveness":{"score":99,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.993,"p_room":1,"age_days":1,"expected_fill_days":30,"reasons":["conf:3","wave","velocity","win:early","comp:brand"],"computed_at":"2026-10-22T06:10:10Z"},"pay":null,"html_url":"https://alion.io/job/hcltech-technical-architect-55","json_url":"https://alion.io/job/hcltech-technical-architect-55.json","meta":{"generated_at":"2026-10-22T11:34:55Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per 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