Data Engineer For Ai Systems

Act digital designs semantic data layers and knowledge base solutions that power enterprise-scale artificial intelligence systems.??????- Design graph schemas, entity resolution strategies, ontological structures, and semantic indexing systems to support agentic AI- Ingest and transform structured and unstructured data from S3, SharePoint, FileNet, and other sources while ensuring semantic consistency- Create taxonomies and ontologies using RDF, OWL, and SKOS standards- Operate and orchestrate AWS services including S3, Glue, Aurora PostgreSQL, Neptune, and AWS Bedrock- Build RAG pipelines, semantic search, metadata enrichment, and Text-to-SQL interfaces- Design graph retrieval strategies combining pattern matching, vector search, full-text search, and relational traversals- Ensure quality control, monitoring, and production readiness of AI data infrastructure??????????- 4-5 Years of experience in Data Engineering, Software Engineering, or AI Engineering with solutions deployed in production- Advanced Python (P3 - Advanced) and SQL proficiency- Practical experience modeling and developing queries with Gremlin, SPARQL, and/or Cypher- Solid AWS experience with S3, Glue, and Aurora PostgreSQL- Experience designing batch and incremental ETL/ELT pipelines- Experience with Docker, CI/CD, and Git- Experience with hybrid retrieval architectures combining SQL, graph, and vector search- Knowledge of data lineage, cataloging, metadata management, and data quality frameworks- Degree or Master’s in Computer Science, Mathematics, Physics, Engineering, or a related field- Spanish at C1 (Expert) level- English at B2 (Advanced) level- Nice to have: Neptune and AWS Bedrock???????Hybrid schedule with 40% telework / remote work; Office schedule.#J-*****-Ljbffr

??????- Design graph schemas, entity resolution strategies, ontological structures, and semantic indexing systems to support agentic AI- Ingest and transform structured and unstructured data from S3, SharePoint, FileNet, and other sources while ensuring semantic consistency- Create taxonomies and ontologies using RDF, OWL, and SKOS standards- Operate and orchestrate AWS services including S3, Glue, Aurora PostgreSQL, Neptune, and AWS Bedrock- Build RAG pipelines, semantic search, metadata enrichment, and Text-to-SQL interfaces- Design graph retrieval strategies combining pattern matching, vector search, full-text search, and relational traversals- Ensure quality control, monitoring, and production readiness of AI data infrastructure??????????- 4-5 Years of experience in Data Engineering, Software Engineering, or AI Engineering with solutions deployed in production- Advanced Python (P3 - Advanced) and SQL proficiency- Practical experience modeling and developing queries with Gremlin, SPARQL, and/or Cypher- Solid AWS experience with S3, Glue, and Aurora PostgreSQL- Experience designing batch and incremental ETL/ELT pipelines- Experience with Docker, CI/CD, and Git- Experience with hybrid retrieval architectures combining SQL, graph, and vector search- Knowledge of data lineage, cataloging, metadata management, and data quality frameworks- Degree or Master’s in Computer Science, Mathematics, Physics, Engineering, or a related field- Spanish at C1 (Expert) level- English at B2 (Advanced) level- Nice to have: Neptune and AWS Bedrock???????Hybrid schedule with 40% telework / remote work; Office schedule.