Gig
$10-$15 per hour
15
Jun 13, 2026
Channel Niche Notice: We run a high-volume media network deeply rooted in Biblical history, archaeology, and ancient Near Eastern narratives, with active plans to expand into broader historical eras (the Middle Ages, Roman history, etc.). A strong familiarity with, or a deep interest in, Biblical texts, theology, and ancient historical analysis is highly advantageous for this role.
Job Description:
PLEASE READ THIS FIRST: We are NOT looking for a traditional creative scriptwriter. We do not want someone to sit down at a blank page and type essays from scratch. That slows down our pipeline.
Instead, we are looking for a highly analytical Prompt Engineer & Script Quality Controller to oversee our automated historical media pipeline.
Our Content Factory utilizes advanced AI systems to handle high-volume script generation and deep historical research extraction. Your core mission is two-fold:
Front-End Engineering: You will actively develop, test, and write advanced system and API prompts to ensure our AI engines output structurally elite first drafts.
Back-End Quality Control: Once the scripts are generated by your prompts, you will act as the human firewall—checking, refining, and verifying the final text to ensure it strictly meets our high narrative and accuracy standards before going to production.
Please note: To prove you are reading carefully, you must include the word ANCIENT as the final word of your application message.
Key Responsibilities:
Prompt Optimization: Write and iterate complex system/API prompts (using frameworks like Claude and OpenAI) to force the AI to natively output specific audience retention mechanics (psychological open loops, micro-hooks every 45 seconds, cliffhangers, and perfect narrative pacing).
Output Quality Control: Methodically audit the AI-generated script outputs. If the AI text drops in quality, you fix the text manually for production, and then immediately re-engineer the system prompts so the machine doesn't make the same mistake twice.
Accuracy Verification: Ensure that the engineered prompts extract and maintain profound historical and archaeological accuracy without losing narrative tension.
Data-Driven Iteration: Cross-reference YouTube Studio retention graphs with our script templates to identify where viewers get bored, and systematically update the prompt logic to fix those specific algorithmic leaks.
Requirements:
Proven experience writing advanced, structured prompts for LLMs/AI systems (Claude, ChatGPT, or APIs) to output specific formatting and behavioral constraints.
Exceptional analytical editing skills. You look at a script like a machine and know exactly when a paragraph will cause a viewer to click away.
Solid understanding of YouTube analytics (specifically AVD, retention charts, and viewer drop-off psychology).
Flawless written English and an eagle eye for pacing, conversational flow, and structural narrative tension.
Rate, Type & Career Growth:
Immediate Start: This begins as a project-based paid trial, estimated at 15–20 hours per week to evaluate your prompt mechanics and structural script approach.
Long-Term Trajectory: While this is a part-time gig at the very start, we are looking for a long-term strategic partner. If your prompt engineering and quality checks successfully move our target tracking metrics, this will transition into a permanent, consistent part-time or full-time strategic role as we scale our network.
Compensation: $10.00 – $15.00 USD/hour (negotiable based on your proven track record with YouTube retention analytics and prompt engineering).
How to Apply (Strict Instructions — Failure to follow means instant rejection):
To apply, you must strictly follow these 3 steps:
Start the very first line of your cover letter with the word "STRATEGY".
Provide a link to a short 60-second audio or video recording (using free tools like
Answer this specific diagnostic question: If a long-form video starts with a healthy 70% retention in the first 30 seconds, but suddenly drops sharply by 30?tween the 1-minute and 2-minute mark, what did the script structurally fail to do, and what specific instruction would you add to the AI prompt to prevent this from happening?