Rafael E.

Key Skills

Software

No software listed

Top Subject Matter

AI product engineering

predictive analytics

Recommendations Domain Expertise

Top Data Types

Image

Text

Document

Top Task Types

Data Collection

Freelancer Overview

Senior Full-Stack Engineer in Contract Review, Compliance, and Legal Research. Brings 14+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Master of Science in Computer Science, Universidad de los Andes (2013). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Data Collection.

Labeling Experience

Senior Full-Stack Engineer | NovaAI Solutions | AI implementation and AI data/ETL pipeline engineering (Jan 2022 - Present)

Data Collection

Led AI implementations for fintech products, including predictive analytics and recommendation workflows processing large record volumes. Built and orchestrated data integrations and ETL pipelines to transform and prepare data for AI system consumption. Contributed to production-ready AI backend services and API-driven data processing. • Engineered REST and GraphQL APIs and background workers to support AI data pipelines. • Implemented ETL workflows and data integrations across internal and external services. • Operated CI/CD for secure AI-enabled deployments and automated releases. • Optimized API response time using profiling, caching, and query optimization.

2022 - Present

AI Engineer & Backend Developer | TechVision BV | AI service and dataset-to-model workflow engineering (Mar 2016 - Apr 2019)

Data Collection

Built backend and AI service foundations for analytics-heavy applications, translating data requirements into production-ready APIs and model workflows. Engineered multiple AI-focused Python APIs and scheduled jobs to process datasets into model-ready exports. Deployed machine-learning prototypes for use cases such as fraud detection, predictive analytics, NLP, and image recognition. • Processed datasets of 5M+ entries through ingestion, cleaning, transformation, and scheduled exports. • Developed reusable service layers, API patterns, documentation, and integration guides for downstream endpoints. • Tuned SQL queries and indexing strategies to shorten analytics report generation time. • Partnered with product and data stakeholders to convert business requirements into AI-system deliverables.

2016 - 2019

Education

Work History