About This Role
This Data Architect role focuses on designing AI and data architectures, particularly with semantic AI, for a leading client in the banking sector. The position involves defining end-to-end architectures, semantic models, and knowledge graphs to integrate structured and unstructured data with advanced AI solutions.
Responsibilities
- Design AI and Data architectures: define end-to-end architectures to integrate structured and unstructured data sources with advanced Artificial Intelligence solutions
- Semantic architecture: design semantic models, ontologies, and knowledge structures that allow representing business entities, concepts, attributes, and relationships
- Knowledge Graphs: design and implement architectures based on knowledge graphs to represent complex relationships, facilitate inference, and improve contextualized access to information
- RAG and Graph RAG architectures: design information retrieval solutions for LLMs, combining semantic search, vector retrieval, metadata, and relationships between entities
- Data architecture: define data integration, transformation, and exposure patterns, including processing pipelines, data models, and interoperability mechanisms between systems
- Technology selection: evaluate and define the most suitable technologies for the solution, including vector databases, graph engines, semantic technologies, and cloud platforms
- API design and integration: establish access and integration mechanisms between data components, semantic services, and AI applications
- Data governance and quality: define criteria for traceability, consistency, cataloging, security, and knowledge management
- Prototyping and implementation: actively participate in proof-of-concepts, technical validations, and development of critical architecture components
- Optimization and technological evolution: analyze the performance, scalability, latency, and costs of solutions, identifying opportunities for improvement
- Definition of technical standards: prepare architecture documentation, technical specifications, design patterns, and best practices for development teams
Requirements
- 5+ years of professional experience in designing data architectures, Artificial Intelligence solutions, or knowledge management platforms
- Solid knowledge of Python, SQL, data modeling, and software architecture design
- Experience in semantic modeling, knowledge representation, ontologies, or domain model design
- Knowledge of Cloud architectures and managed data and AI services in AWS, Azure, or Google Cloud
- Practical knowledge of semantic technologies such as RDF, OWL, and SPARQL
- Experience with Knowledge Graphs and graph database technologies, such as Neo4j or other equivalent solutions
