Python Team Lead

About this role

In this hourly, remote contractor role, you will work as a Python (Generalist) Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across Python AI training projects. You will review AI-generated Python code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected quality standards.

Python, Debugging, Backend Development

Responsibilities

• Spot-check Python items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues.
• Review AI-generated Python code, debugging responses, algorithms, backend snippets, automation scripts, tests, and explanations.
• Update trainers/QAs on Discord about guidelines, workflow updates, and Python-specific quality expectations.
• Respond to questions around Python syntax, runtime behavior, exceptions, package usage, testing, typing, security, performance, and rubric interpretation.
• DM inactive contributors, encourage activation, track follow-ups, and flag availability issues.

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Information Technology, or equivalent professional software engineering experience.
• Strong grasp of the English language to follow guidelines, communicate with teams, and provide clear technical feedback.
• 3+ years of professional experience in Python development, backend engineering, automation, scripting, data workflows, code review, QA, teaching, or technical mentoring.
• Strong understanding of Python fundamentals such as data structures, functions, classes, modules, exceptions, comprehensions, iterators, generators, decorators, context managers, virtual environments, packaging, and testing.
• Ability to evaluate Python content against rubrics and identify issues such as incorrect logic, non-executable code, poor exception handling, inefficient algorithms, unsafe file/network operations, hallucinated APIs, or incomplete explanations.