I am a Senior AI Engineer with a strong background in Python, LLMs, RAG, Azure, and data engineering. I focus on building practical AI systems that improve retrieval quality, automate workflows, and make large-scale document and data pipelines more reliable.
In my current role at TELUS Digital, I work remotely on agentic AI workflows, hybrid retrieval, and Azure AI Search optimization. I have improved answer precision, reduced manual orchestration, and helped create AI-ready file access pipelines that lower latency and improve search performance.
Previously, I worked as a Data Engineer at AB InBev, where I automated pipeline orchestration, schema generation, and metadata documentation. I also implemented data-quality monitoring and reporting to improve issue detection across analytical workflows.
Before that, I served as a Partner Integration Software Developer at Aqfer, designing and optimizing ingestion pipelines and REST APIs across multiple cloud environments. I led integrations across heterogeneous data sources and helped improve processing efficiency and data availability.
I also have experience as a Java Cloud Application Developer at Itlize, where I built cloud-based data pipelines and ingestion services using Java, Spring Boot, MySQL, and AWS. My work has consistently centered on scalable systems, automation, and high-quality engineering practices.
I hold a BS in Electrical and Computer Engineering with a minor in Applied Mathematics from the New York Institute of Technology, graduating Summa Cum Laude. I am fluent in English and Portuguese, and I also speak Spanish at an intermediate level.
GPA: 3.9, Summa Cum Laude
Improved RAG answer precision by 35-50% using contextual and hybrid retrieval; built agentic AI workflows with Azure AI Foundry Agent SDK; optimized Azure AI Search indexing strategies; designed AI-ready file access pipelines; automated provisioning via Terraform.
Automated pipeline orchestration, schema generation, and metadata documentation in Python and Databricks; implemented automated data-quality monitoring and reporting using SQL, Azure, and Slack.
Designed and optimized high-performance ingestion pipelines and REST APIs using Java, Python, Scala, and Go; led ingestion and integration of 10+ heterogeneous data sources across AWS and GCP; refactored legacy data connector framework.
Developed cloud-based data pipelines and ingestion services using Java, Spring Boot, MySQL, and AWS with focus on data quality, scalability, automated testing, and high-performance querying.
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