Irene De Nevi

I’m an AI Data Engineer with extensive backend development experience and a focus on scalable data platforms. I’m passionate about building business-oriented AI products with measurable impact, and I bring experience spanning data engineering, microservices, workflow orchestration, and applied AI solutions.

In my current role, I work as part of a team of three engineers on a large-scale enterprise data platform dedicated to insurance analytics. I design and optimize data ingestion pipelines for tabular data and flat files from cloud and on-premises sources into on-premises Oracle databases, processing over 1 TB of data per day with Apache Airflow, Python, and Oracle GoldenGate Replicat—while supervising and maintaining over 30 active processes with monitoring via Grafana.

I also build reliable systems around deployment and automation, using CI/CD practices with Python, Scala, Bash, Java, Jenkins, and Terraform, and I strengthen production delivery with CI/CD and monitoring tooling. Alongside engineering, I develop applied AI capabilities such as an AI coding assistant using LangChain, LangGraph, HuggingFace, and Chroma, and I’ve led RAG and speech transcription work (HuggingFace LLM models, Docling/LC framework, and Whisper) within microservices ecosystems for real-time analytics and observability.