Knowledge Engineering Solution Architect Associate Director

Accenture Plc

  • Morristown, NJ
  • 5 days ago

    Highlights

    The Work: 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. 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.

    Numbers & Facts

    LocationMorristown, NJ

    Description

    About Accenture:

    Accenture helps the world's leading enterprises reinvent by building their digital core and unleashing the power of AI to create value at speed for organizations across industries. Our strategy is to be the reinvention partner of choice for our clients and lead in the safe, widespread adoption of AI, and to be the most client-focused, AI-enabled, great place to work in the world. We bring together the talent of our approximately 814,000 people with proprietary assets and platforms, deep process and industry expertise, and leading ecosystem relationships to deliver end-to-end solutions and measurable outcomes at scale. Through our Reinvention Services, we offer broad expertise across Cybersecurity, Digital Core, Finance, Industry and Enterprise, Song, Supply Chain and Engineering, and Talent, with advanced capabilities in AI and Data, Industry and Process, and Technology. We serve approximately 9,000 clients and generated approximately $74 billion in FY26 revenue. Visit us at accenture.com.

    We Are:

    Accenture is recognized as a global leader in AI and cloud transformation, helping businesses across industries reimagine the digital core for an AI-native operating model. Through partnerships with frontier AI labs such as Anthropic and OpenAI, and the leading cloud providers, Accenture delivers end-to-end services that drive innovation and business agility.

    The Digital Core Reinvention practice does work few others attempt: methodically excavating what is actually inside an enterprise's code and process before anyone dares to transform it. Code Archaeology is that discipline - AI agents digging through millions of lines of legacy so the transformation stands on evidence, not folklore.

    You Are:

    You are the practice's senior, client-facing authority on enterprise ontologies, knowledge graphs, and semantic architectures. You work directly with client executives, domain subject matter experts (SMEs), and engineering leaders to design scalable Domain Intelligence (DI) and GraphRAG solutions.

    The Work:

    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.

    Travel may be required for this role. The amount of travel will vary from 0% to 100% depending on business need and client requirements.

    Similar Jobs