Senior Consultant – Semantic Data & AI Engineering
Tasks
- Apply SHACL validation
- Build semantic layers and ontologies
- Build semantic search solutions
- Conduct performance testing and production deployment
- Create APIs and services
- Create automated tests
- Create data pipelines
- Design knowledge graphs
- Develop NLP entity extraction and linking
- Develop Python or Java data transformations
- Develop semantic data models
- Facilitate requirements and modeling sessions
- Implement confidence scoring
- Implement retrieval-augmented generation
- Implement semantic data quality controls
- Integrate Knowledge Graphs with Generative AI
- Lead technical workstreams
- Manage provenance and lineage
- Mentor junior consultants and engineers
- Perform relationship extraction and classification
- Produce technical designs and deployment documentation
- Support CI/CD and monitoring
- Support data retrieval for model evaluation and inference
Perks/Benefits
- 401k match
- Commuter benefits
- Dependent care
- FSA
- HSA
- Maternity leave
- Medical/Dental/Vision
- Paternity leave
- Tuition reimbursement
- Wellness reimbursement
Skills/Tech-stack
API Development | AWS | Agile | Amazon Neptune | Automated testing | Azure | BigQuery | CI/CD | Classification | Containers | Data Governance | Data Pipelines | Data Validation | Data integration | Databricks | Embeddings | Entity Extraction | Entity Linking | Generative AI | Git | Google Cloud | GraphDB | GraphRAG | JSON-LD | Java | Knowledge graphs | LLM | Lakehouse Architecture | Machine Learning | NLP | Neo4j | OWL | Python | RAG | RDF | RDFS | Redshift | Relationship Extraction | Retrieval-Augmented Generation | SKOS | SPARQL | Semantic Modeling | Semantic Search | Shacl | Snowflake | Stardog | Turtle | Vector Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Regions
Countries
States
Cities
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