Principal Consultant – Semantic Data & AI Engineering
Tasks
- Acquire transform map validate and load data
- Build semantic data pipelines
- Define semantic data quality controls
- Design knowledge graphs
- Develop Python and Java services and APIs
- Evaluate and recommend AI frameworks
- Evaluate and recommend graph databases and vector databases
- Implement NLP and entity extraction
- Implement data provenance lineage and governance
- Implement generative AI vector search and GraphRAG
- Implement relationship extraction and semantic enrichment
- Implement semantic layers and ontologies
- Integrate knowledge graphs with AI and machine learning
- Lead technical workshops and architecture decisions
- Mentor team members on semantic design patterns
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | AWS | Agile | Amazon Neptune | Azure | CI/CD | Cloud Platforms | Data Governance | Data Lineage | Data Modeling | Data Pipelines | Data Quality | Data provenance | Entity Extraction | Git | Google Cloud | Graph Databases | GraphDB | GraphRAG | JSON-LD | Java | Knowledge graphs | LLM | Language Processing | Machine Learning | Natural Language | Natural Language Processing | Neo4j | OWL | Ontologies | Python | RAG | RDF | RDFS | Relationship Extraction | SKOS | SPARQL | Semantic data | Semantic data modeling | Shacl | Stardog | Taxonomies | Vector Databases | Vector Search
Education
N/A
Roles
AI | AI Engineer | Consultant | Data Engineer | Engineer | Principal | Principal Consultant
Regions
Countries
States
Cities
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