Architected high-throughput Reinforcement Learning Gym environments in Python to evaluate and optimize backend AI model workflows for major LLM providers.

Building full-stack applications with Python, TypeScript, Node.js, and React, delivering end-to-end solutions across the stack for RLHF training pipelines.

Developing RL gyms for AI models to learn how to navigate complex web and local machine environments, enabling advanced agentic reasoning capabilities.