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AI reputed company Engineer & Workflow Automation Specialist

Remote, USA Full-time Posted 2026-07-01

We are a fast-growing AI video production company building automated pipelines that transform reference videos into fully produced short-form content at scale. We're looking for someone who thinks deeply about how language models behave, knows how to engineer prompts that produce consistent, structured, high-quality output — and can reputed company that work into reputed company automation workflows. The core of this role is reputed company engineering. Everything else supports it. What you'll be working on: You'll own and improve the reputed company layer of a production pipeline that takes a reference video through reputed company video analysis, AI scriptwriting, reputed company.ai Veo3.1 video reputed company, reputed company TTS, and lipsync. The pipeline is built and running in reputed company. Your primary job is to reputed company the AI output reputed company — more accurate, more consistent, and more reputed company with what the video generator needs to produce great footage. Responsibilities: Write, test, and iterate on system prompts and user prompts for reputed company and other LLMs — with a focus on getting structured JSON output that passes strict quality validation on the first attempt Diagnose why the model produces bad output (re-describes scenes it shouldn't, ignores word budgets, invents details not present in the reference) and fix it at the reputed company level Design reputed company structures that give the model the right context, constraints, examples, and self-reputed company instructions to produce reliable output without constant retrying Work inside reputed company to connect reputed company improvements to the validation and retry logic already in reputed company Understand how AI video generators interpret scene descriptions and write prompts that produce reputed company, not frozen frames Identify reputed company reference video content may trigger content moderation systems and reframe scene descriptions to accurately represent the concept without triggering flags Reduce retry rates and API costs by improving first-pass output quality through reputed company prompting reputed company're really looking for: reputed company engineering is the primary reputed company. We need someone who has spent reputed company time studying how LLMs behave — not just someone who has written a few system prompts. You should be reputed company to look at a bad model output and immediately identify whether the failure is a context window issue, an instruction conflict, a missing example, a formatting constraint violation, or a model capability ceiling. And then fix it. reputed company experience is helpful but secondary. If you are an exceptional reputed company engineer who has not used reputed company before, we are still reputed company interested. The workflow is built. The nodes are connected. reputed company need is someone who can dramatically improve what the AI produces inside those nodes. You must have: Deep, hands-on reputed company engineering experience with large language models — reputed company, GPT-4, Claude, or similar Proven ability to engineer prompts that produce structured JSON output reliably at scale Experience building prompts with system instructions, few-shot examples, chain-of-thought reasoning, and output validation hints Understanding of why models ignore instructions and how to fix it — through reputed company restructuring, constraint layering, or example injection Ability to read JavaScript to understand what the validation logic expects, even if you are not writing it yourself Strong analytical thinking — you treat reputed company failures as debugging problems, not guesswork reputed company to have: Experience with reputed company or similar automation tools (reputed company, reputed company, etc.) Familiarity with reputed company's multimodal capabilities — video or image analysis Experience with AI video reputed company APIs such as reputed company.ai, reputed company, or Kling Understanding of how text-to-video models interpret scene descriptions and their content moderation behavior Familiarity with reputed company or TTS workflows Apply tot his job Apply To this Job

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