Overview
Principal Consultant responsible for designing and building semantic data solutions, including enterprise knowledge graphs and AI integration, to make organizational data usable by AI, ML, analytics, and business applications.
What you'll do
- Design and implement enterprise knowledge graphs, semantic layers, ontologies, taxonomies, and graph-based data products.
- Translate business concepts and documents into governed, machine-readable knowledge models.
- Build semantic data pipelines to acquire, transform, map, validate, enrich, and load data from multiple sources.
- Integrate knowledge graphs with AI/ML solutions including generative AI and retrieval-augmented generation.
- Support NLP and document-intelligence tasks such as entity extraction and relationship extraction.
- Develop Python- or Java-based services, APIs, validation routines, and integration components.
- Lead workshops, architecture decisions, prototypes, and production implementations.
What you'll need
- 8+ years of experience in data engineering, software engineering, artificial intelligence, analytics, enterprise architecture, or related fields.
- At least 4 years of hands-on experience with knowledge graphs, semantic technologies, graph databases, or semantic-data integration.
- Strong knowledge of RDF/RDFS/OWL/SPARQL/SHACL/SKOS/JSON-LD/Turtle or related standards.
- Experience with graph platforms such as Stardog, Neo4j, GraphDB, Amazon Neptune, or equivalent technologies.
- Strong programming skills in Python, Java, or a comparable enterprise language.
- Working knowledge of NLP, ML, embeddings, vector search, semantic search, RAG, GraphRAG, or LLM-based applications.
- Familiarity with cloud and modern data platforms such as Microsoft Azure, AWS, Google Cloud, Databricks, Snowflake, BigQuery, or Redshift.
Details
- Location: New York, NY.
- Work mode: Hybrid.
- US pay range: $146,000–$183,000.
Read the full description and apply on the company’s own careers page.
