Knowledge Graph Architect for Enterprise AI

Accenture; Irving (TX); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Medical benefits

401(k) plan

Paid time off

Job summary

Accenture in Dallas, TX is seeking a Knowledge Architect to design and govern enterprise-scale knowledge graphs, ontologies, and semantic data models for next-generation agentic AI systems.

You will embed with clients as a trusted technology advisor, lead data modeling, and collaborate with AI/ML teams to power RAG pipelines, multi-step reasoning, and scalable graph architectures across domains.

Qualifications

• Bachelor's degree or equivalent (minimum 12 years' work experience).
• 4+ years of experience in Knowledge Graph technologies (e.g., RDF, SPARQL, Gremlin, LPG, SHACL, RDFS)
• 2+ years of experience with schema design, ontology management, and Knowledge Graph curation
• 2+ years of experience in semantic modeling and linked data principles
• 2+ years of experience designing and developing knowledge graph solutions and graph-based ML models
• 2+ years of experience with relational databases, object stores, graph databases (e.g., Stardog, Neo4j, Amazon Neptune, TigerGraph), and vector databases
• 2+ years of experience in agentic pipeline design (LangChain, LlamaIndex, AutoGen)

Responsibilities

• Own the end-to-end design, governance, and maintenance of enterprise-scale knowledge graphs and ontologies, bridging structured domain knowledge with large-scale agentic AI pipelines to enable reasoning, planning, and decision-making.
• Develop and govern ontologies, taxonomies, and semantic data models that formalize domain knowledge and support interoperability across systems and teams.
• Define and enforce data modeling standards, schema design patterns, and best practices for structured and semi-structured knowledge representation.
• Translate complex domain knowledge from subject matter experts into formal, machine-readable knowledge structures using RDF, OWL, SPARQL, or property graph models.
• Lead knowledge engineering discovery workshops and working sessions with client stakeholders to surface, validate, and formalize domain knowledge requirements.
• Collaborate with AI/ML engineers to integrate knowledge graphs as grounding and context layers for LLM-based agentic pipelines and retrieval-augmented generation (RAG) systems.
• Design knowledge structures that support multi-step agent reasoning, tool use, and dynamic planning across heterogeneous data sources.
• Work with project teams, team leaders, delivery leads, and client stakeholders to create standout Data & AI offerings powered by graph-based technologies.
• Collaborate with data engineering and platform teams to build scalable pipelines for knowledge graph population, enrichment, and lifecycle management.
• Develop strong client relationships and earn the trust of key stakeholders as a strategic advisor.
• Communicate complex ontological concepts and graph architectures clearly to both technical and non-technical audiences.
• Evaluate and pilot emerging tools, frameworks, and standards (e.g., LPG vs. RDF, Wikidata, schema.org, W3C standards).

Skills

Ontology design

Taxonomy development

Semantic modeling

Schema design

RDF/OWL

SPARQL/Cypher/Gremlin

Graph databases

Python

REST APIs

Cloud platforms

Education

Bachelor's degree or equivalent

Tools

Neo4j

Amazon Neptune

TigerGraph

Stardog

RDFLib

Job description

Accenture in Dallas, TX is seeking a Knowledge Architect to design and govern enterprise-scale knowledge graphs, ontologies, and semantic data models for next-generation agentic AI systems.

You will embed with clients as a trusted technology advisor, lead data modeling, and collaborate with AI/ML teams to power RAG pipelines, multi-step reasoning, and scalable graph architectures across domains.