Erion Criscente

Erion Criscente works primarily in Python (Django, FastAPI) and TypeScript (React, Next.js), with AWS serverless (Lambda, DynamoDB, S3, SQS) in the cloud and MLflow for production MLOps. He also uses Node.js and Docker. He is a Senior Software Engineer at Pearson and completed a postgraduate program in Machine Learning and Artificial Intelligence at Faculdade XP Educação (IGTI).

At Pearson, Erion provides technical leadership on a student-facing learning platform: architecture decisions, code review, and hands-on delivery. In his earlier Pearson roles (2023–2025) he maintained legacy applications and built new APIs and serverless microservices on AWS Lambda, DynamoDB, S3, and SQS. At Wiise Well (2025–2026) he built the software and MLOps infrastructure around failure-prediction models for offshore equipment: MLflow model lifecycle and model bank, deployment, and integration into business systems. Before that he was the lead developer of the first Brazilian dynamic innovation management platform (Lotik), and he co-founded and helped lead a web3 hosting service that was acquired in 2023. He has also implemented secure API authentication (JWT, OAuth2).

You can connect with Erion through his LinkedIn profile or via the contact form at erion.dev. He's interested in discussing technology trends, sharing knowledge about web development, cloud architecture, and machine learning. He enjoys connecting with fellow developers and tech professionals globally, communicating in English and Portuguese.

Erion has hands-on experience with AWS serverless architecture, including Lambda functions, DynamoDB databases, S3 storage, and SQS message queues. At Pearson he built APIs and serverless microservices on this stack for a student-facing education platform, focusing on scalability, cost optimization, and performance. He also implements CI/CD pipelines and infrastructure as code.

Yes. In production, at Wiise Well (2025–2026), Erion built the software and MLOps infrastructure around failure-prediction models for offshore equipment: MLflow model lifecycle and model bank, deployment, and integration into business systems. He completed a postgraduate program in Machine Learning and Artificial Intelligence at Faculdade XP Educação (IGTI) (August 2025 – February 2026), covering modern AI technologies including Generative AI, LLM operations, and Advanced Data Engineering. He placed 22nd of 371 (Top 6%) in the Kaggle competition SPR 2026 Mammography Report Classification.

At Pearson, Erion provides technical leadership on a student-facing learning platform: architecture decisions, code review, hands-on delivery, and technical alignment with the product team. He also brings production MLOps experience, which comes from his previous role at Wiise Well — where he built the software and MLOps infrastructure around failure-prediction models for offshore equipment (MLflow model lifecycle and model bank, deployment, and integration into business systems) — and from personal projects, not from his work at Pearson. His AWS serverless depth (Lambda, DynamoDB, S3, SQS) comes from his earlier Pearson backend roles, where he implemented the engagement microservice behind an initiative that raised student course completion from 30% to 70%.

Erion is based in Monte Alto, São Paulo, Brazil, and has worked on internationally distributed teams. He has experience with remote collaboration and can work across different time zones. He communicates fluently in English and Portuguese.