Senior AI Data Engineer
Tasks
- Apply DataOps including testing monitoring lineage tracking and SLAs
- Build knowledge graphs and manage graph schemas queries and ingestion pipelines
- Build observable data pipelines from upstream data sources
- Collaborate with ontologist to maintain domain intent fidelity
- Design embedding pipelines for financial and regulatory data
- Embed semantic models into APIs and data contracts
- Ensure scalability of semantic layer systems
- Evaluate and integrate LLM tooling frameworks
- Implement RAG architectures for LLM grounding
- Implement semantic layer models into production systems
- Operate vector database infrastructure
- Resolve cross domain data integration challenges
- Support application teams in adopting AI ready data products
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | AWS | Amazon Neptune | Azure | Bounded Contexts | Cloud platform | DDD | Data Contracts | Data Engineering | Data Lineage | Data Observability | Data Testing | DataOps | Domain-Driven Design | Embeddings | Google Cloud | Google Cloud Platform | Graph Database | JSON-LD | Jena Fuseki | Knowledge graphs | LLM Pipelines | Neo4j | OWL | PGVector | Pinecone | Python | Qdrant | RAG | RDF | RDF stores | Retrieval-Augmented Generation | SKOS | Vector Databases | Weaviate
Education
N/A
Roles
AI | AI Data Engineer | Data Engineer | Engineer | Senior AI Data Engineer
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