Thomas Maloney

Architected and implemented scalable backend systems using Python, Golang and Node.js, enabling secure, real-time data processing and API integration for enterprise-grade applications. Built and deployed LLM-powered solutions using retrieval-augmented generation (RAG) with Elasticsearch to ground large language models on precise, up-to-date knowledge for conversational AI and intelligent automatio

Developed scalable microservices and APIs using Golang frameworks like Gin and Echo, enabling secure, real-time data exchange between healthcare providers and third-party systems. Optimized database performance by leveraging PostgreSQL and MongoDB for structured and unstructured data storage, reducing query execution times by 40% and enabling seamless handling of datasets exceeding 6TB.

Architected a new backend system, building API structures, database architecture, CI/CD, and unit testing pipelines from scratch, supporting seamless integration, increasing integration efficiency by 35%, and scalability across platforms. Designed and launched a real-time analytics dashboard using Django and React, enabling stakeholders to make data-driven decisions and increasing user engagement

Developed a custom Python-based web scraping tool that automated data collection from 50+ sources, reducing manual effort by 80% and improving data accuracy by 95%. Developed and maintained a Python-based software system that processed and analyzed large datasets, resulting in a 50% reduction in data processing time and a 40% increase in data accuracy.

Completed a Bachelor of Computer Science, focusing on core computer science principles. Gained foundational knowledge and practical skills in software development and related technologies.