Ralph Lugue

Joined as a contract senior engineer on a Healthcare SaaS platform with AI-assisted clinical workflows, Designed and developed backend services and APIs using Python (FastAPI) and Node.js (NestJS), Built and maintained frontend applications using React, focusing on performance and usability for clinicians, Integrated Python-based ML inference services (scikit-learn, spaCy) into existing backend systems via secure, scalable REST APIs, Collaborated with data science teams to deploy and maintain AI-assisted features in production, Delivered features end-to-end in a fully remote, Agile environment

Designed and developed full-stack Fintech applications supporting consumer credit and merchant platforms, Built backend services using Python (Django) and Node.js (Express) to handle core business logic, APIs, and third-party integrations, Developed frontend features using Angular, later transitioning to React, with a focus on usability and performance, Implemented REST APIs for payments, user onboarding, and internal operational tools, Collaborated closely with product, risk, and operations teams to deliver production features, Contributed to system reliability, data accuracy, and secure handling of financial information.

Built and maintained backend services using Python (FastAPI) and Node.js (NestJS) to support core features of an AI-driven contract lifecycle management platform, Integrated AI-powered contract analysis services to extract metadata, risk scores, and search insights from large volumes of legal agreements, leveraging machine learning and NLP-based APIs, Developed responsive user interfaces with Next.js and React, focusing on efficiency and usability for enterprise legal and operations teams, Implemented REST APIs and asynchronous task processing using Redis and background workers for high-throughput document workflows, Collaborated with cross-functional teams including product owners, QA, and data engineers to deliver reliable, scalable SaaS features in production, Worked in cloud environments using AWS (EC2, S3, RDS) with containerized development and deployment workflows

Designed and implemented scalable backend services using Python (FastAPI) and Node.js (NestJS) to support high-volume enterprise clients, Built and maintained modern frontend applications using React and Next.js, improving performance and maintainability across core modules, Integrated machine learning inference services (document classification, data extraction pipelines) into backend systems via secure REST APIs, Implemented asynchronous processing using Celery and Redis to handle background tasks and large document workloads, Contributed to cloud infrastructure on AWS (EC2, RDS, S3, Lambda) and containerized services using Docker, Participated in system design discussions, code reviews, and mentoring of junior engineers within a fully remote engineering team