Write robust, scalable, and production-ready Python code, Provide code reviews, guidance, and mentorship to fellow developers to maintain high coding standards, Write unit tests and integration tests (unittest, pytest, etc.), Design, engineer, and optimize features in the digital twin for Reinforcement Learning (RL) simulations using Python (Python data structures, NumPy, Pandas, etc.), Create, optimize, and maintain training and evaluation scripts (for RL agents), Set up and maintain Python environments using modern tools (uv, conda, etc.), Work collaboratively using git (GitHub), Participate in customer calls to understand and translate requirements into actionable technical features., Brainstorm ideas to improve the RL agent, including algorithms, rewards, and architecture.