Artificial Intelligence Architect ( Ontology)

Experience:

Share your updated CV at: tjaya@kpmg.com

Role Overview

Ontology Engineer (Associate Director level)

You will architect enterprise-scale ontologies, build Knowledge Graphs, integrate them with AI systems, and establish global standards for semantic consistency.

Key Responsibilities

1. Semantic Architecture

• Lead the design and development of

  enterprise-scale ontologies, taxonomies, and knowledge graphs

  .
• Build semantic structures that serve as the ground truth for

  LLM-based and AI-driven applications

  .

2. Hands-on Development

• Develop and maintain ontologies using

  OWL, RDF, SPARQL, SKOS

  and ontology modeling tools (e.g., Protg, TopBraid).
• Integrate semantic layers with enterprise platforms like

  Snowflake, Databricks

  , and other data engineering ecosystems.

3. LLM & Knowledge Graph Integration

• Architect

  GraphRAG

  solutions combining Knowledge Graphs with LLMs.
• Improve explainability, reduce hallucinations, and enhance contextual accuracy for Generative AI applications.

4. Standardization & Governance

• Define enterprise standards for

  data modeling, semantic consistency, and ontology governance

  across global service lines.
• Lead evaluation and selection of graph databases such as

  Neo4j, Azure Cosmos DB (Gremlin/RDF)

  , Stardog, or similar.

5. Cloud & Infrastructure Management

• Design and deploy AI models and services on

  Azure

  , leveraging cloud-native tools.
• Ensure scalability, resilience, reliability, and security of semantic + AI workloads.
• Optimize cost, performance, and resource utilization for large-scale AI deployments.

6. Performance Tuning & Optimization

• Continuously monitor and optimize

  AI/ML pipelines, Knowledge Graph queries, embeddings, and semantic workloads

  .
• Apply techniques like

  hyperparameter tuning, model optimization, and feature engineering

  to drive performance.

Work Experience (Mandatory)

• 12+ years

  in Data Engineering / Information Architecture.

• 6+ years

  hands-on experience in

  Ontology Engineering / Semantic Web / Knowledge Graphs

  .
• Proven experience building semantic systems supporting

  AI/ML and Generative AI applications

  .
• Deep experience with

  Azure cloud services

  (AI, Data, Compute, AKS, Functions).
• Strong coding experience in

  Python, Scala, SQL

  , and exposure to ML libraries & big data frameworks.
• Experience working in a

  global, matrixed organization

  with cross-functional technical teams.

Skills (Mandatory)

Semantic & Ontology Skills

• Mastery of

  RDF, OWL, SKOS, SPARQL

• Hands-on with ontology modeling tools:

  Protg, TopBraid

• Expertise in Knowledge Graph design & graph query optimization
• Experience with graph databases:

  Neo4j, Cosmos DB, Neptune, Stardog

  , etc.

AI/ML & NLP Skills

• Strong understanding of

  AI/ML algorithms, vector embeddings, transformer models

• Deep understanding of

  NLP

  and interaction between semantic structures & LLMs
• Knowledge of RAG, GraphRAG, entity linking, semantic search

Cloud & Engineering Skills

• Expertise in

  Azure Cloud Architecture

• Cloud-native development, data pipelines, deployment
• Performance & cost optimization for AI workloads
• Strong Python & SQL proficiency

Leadership & Communication

• Ability to lead and mentor technical teams
• Strong stakeholder communication with senior management
• Ability to articulate business value of complex semantic architectures

Educational Qualifications

• Master’s or PhD

  in Information Science, Computer Science, Knowledge Representation, Computational Linguistics, or related fields.
• Certifications in

  AI/ML, Cloud (Azure), or Data Engineering

  are an added advantage.

Apply Now

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