Manager, AI Engineer KPMG
- $153,710–$267,030 Per Year
| Location | Atlanta, GA |
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Lead AI Engineer with semantic web tech
Remote in Georgia, & 4 others
AI Solution Engineering
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We are seeking a Lead AI Engineer with deep expertise in semantic web technologies to act as the strategic bridge between business stakeholders (Data Governance, Enterprise Architecture, AI/Analytics teams) and technical implementation teams.
In this role, you will define the vision, architect, and drive the enterprise-wide adoption of semantic and data foundations, translating complex business terminology, metadata requirements, and domain concepts into structured ontologies, knowledge graphs, and scalable data pipelines that power Analytics, AI, Agentic AI, Knowledge Management, and digital solutions.
As a technical leader, you will mentor engineers, set standards, and shape the strategic direction of our semantic and knowledge engineering practice.
Responsibilities
Define the strategic roadmap for enterprise semantic and knowledge engineering initiatives, aligning them with long-term business and technology goals
Lead and mentor a team of engineers, fostering technical excellence, knowledge sharing, and professional growth
Lead workshops and discovery sessions with senior business and technical stakeholders to elicit, define, and document business entities, relationships, attributes, hierarchies, and competency questions
Architect and own enterprise ontologies, taxonomies, controlled vocabularies, and semantic models across multiple domains
Establish standards for mapping source systems and business concepts into canonical semantic representations
Define architectural blueprints for scalable ELT/ETL frameworks, graph-loading processes, and semantic transformations supporting structured, semi-structured, and unstructured data
Drive the design and evolution of graph databases, semantic layers, and metadata repositories to directly support RAG (Retrieval-Augmented Generation), Knowledge Graph, and Agentic AI solutions
Establish and chair ontology governance frameworks, business glossary stewardship, and semantic versioning policies at the enterprise level
Define best practices for automated data quality validation, monitoring, lineage, and observability processes
Partner with Data Architects, Solution Architects, Data Stewards, and AI Engineers to ensure semantic consistency, discoverability, and high data quality across all enterprise data products
Represent the organization in cross-functional forums and influence enterprise-wide technical decisions
Requirements
Bachelors or Masters degree in Computer Science, Information Systems, Data Science, Engineering, or a related field
7+ years of combined professional experience in Data Engineering, Data Architecture, Knowledge Engineering, or Semantic Technologies
1+ years of proven experience leading technical teams or initiatives
Deep, hands-on expertise in semantic web technologies (RDF, OWL, SPARQL), along with SKOS and SHACL, ontology development, taxonomy creation, and knowledge graph architecture at enterprise scale
Proven track record of designing and delivering enterprise-scale ELT/ETL pipelines and data integration frameworks
Strong experience with cloud data platforms (Databricks, Snowflake, Azure, or AWS)
Advanced coding skills in Python and SQL, alongside graph querying and reasoning capabilities
Strategic understanding of modern AI patterns, including RAG architectures, vector databases, and LLM integrations, as well as agentic AI systems, with the ability to guide architectural decisions
Comprehensive knowledge of metadata management, data quality, and lineage, along with governance principles and semantic versioning
Demonstrated leadership and mentoring skills, with a history of guiding senior engineers and shaping technical culture
Exceptional verbal and written communication skills, with the ability to articulate complex semantic and data concepts clearly to executive-level, technical, and non-technical audiences
English proficiency at an Upper-Intermediate level (B2) or higher
Nice to have
Experience representing organizations in industry forums, publishing thought leadership, or contributing to open-source semantic technology communities
Advanced background in semantic tech (RDF, OWL, SPARQL), SKOS, SHACL, and Knowledge Graphs
Familiarity with AWS, Neo4j, and Amazon Neptune
Deep expertise in vector databases, semantic layer platforms, and RAG integrations
Experience defining enterprise architecture standards and governance frameworks across multiple business units



