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# Knowledge Engineering Solution Architect Associate Director

- **Company:** Accenture
- **Location:** Houston, TX, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cloud Computing, Graph Database, Internet Security, Python (Programming Language), Neo4j, SPARQL, SQL Databases, Management of Software Versions, Generative AI, Knowledge Engineering, Data Layers, Graph RAG
- **Published:** November 11, 2026
- **Apply:** https://www.careerbuilder.com/job-details/knowledge-engineering-solution-architect-associate-director-houston-tx--adf910cf-e0fa-45f9-93ac-aa8634cef672

## About the Role

Knowledge Engineering, Internet Security, Customer Relations, Artificial Intelligence (AI), Supply Chain, Ecosystems, Finance, Cloud Computing, Archaeology, Artificial Intelligence (AI) Agents

## Description

You remain hands-on: you develop baseline ontology models, establish data quality shapes (SHACL/ShEx), write core SPARQL/Cypher queries, and build prototype data/graph pipelines using Python and SQL/SPARQL. You set modeling standards for engineering teams, author the semantic/knowledge sections of RFPs, lead technical discovery workshops,and create reusable semantic assets that accelerate practice delivery.

Solutioning & Presales Strategy - Lead the knowledge engineering and ontology workstreams for client proposals, including solution architecture, technical approach, staffing models, and effort estimations. Facilitate discovery workshops with business and technical stakeholders to define domain boundaries, high-value use cases, and key performance indicators (KPIs). Build business cases for Knowledge Graphs, Semantic Layers, and Generative AI / GraphRAG architectures-quantifying ROI, defining success metrics, and designing proof-of-concept (PoC) pilots. Present technical architectures during client orals, executive briefings, and vendor evaluations; build interactive modeling demos on sample enterprise datasets. Draft Statements of Work (SOWs), deliverables, and scope guardrails for ontology, graph analytics, and semantic layer implementations.

Ontology & Knowledge System Design

 * Design the upper ontology (meta-model) and establish inheritance and specialization rules across domain and sub-domain ontology modules.
 * Model core domain entities, relationships, attributes, business glossaries, intent taxonomies, and cross-walk mappings to industry standards (e.g., FIBO, SNOMED, W3C standards).
 * Architect bitemporal data models (valid-time and transaction-time) to track historical state changes, schema evolution, and ontology versioning.
 * Define data quality constraints (SHACL), entity resolution frameworks, and semantic governance policies to prevent semantic drift across multi-source integrations.