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Llm Prompt Review Jobs (NOW HIRING)

Diablo Convoy

LLM Engineer

Houston, TX · On-site

$120K - $130K/yr

This role focuses on using artificial intelligence tools, prompt engineering techniques, and ... Review, validate, and refine AI-generated content to ensure accuracy and data integrity * Support ...

H&W Electrical Corporation

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Prompt Engineer

Greenville, SC · On-site

$70K - $115K/yr

... review workflows • Develop and operate internal intelligence tooling that supports business ... Stand up local LLM infrastructure where it makes sense for cost, latency, or data sensitivity ...

Bluefish AI

Customer AI Analyst

New York, NY · Remote

LLM Prompt Optimization - Design, test, and refine prompts to get high-quality outputs from large ... Deliver actionable insights, performance reviews, and monthly deliverables (e.g., reports, strategy ...

Team Red Dog

AI Prompt Engineer

Redmond, WA · Remote

... virtual assistants using LLM and generative AI technologies. * Software Engineering ... reviews, and prompt optimization to improve conversational accuracy, usability, and overall AI ...

Bluefish AI

Customer AI Analyst

New York, NY · On-site +1

LLM Prompt Optimization - Design, test, and refine prompts to get high-quality outputs from large ... Deliver actionable insights, performance reviews, and monthly deliverables (e.g., reports, strategy ...

Team Red Dog

AI Prompt Engineer

Redmond, WA · On-site

... virtual assistants using LLM and generative AI technologies. * Software Engineering ... reviews, and prompt optimization to improve conversational accuracy, usability, and overall AI ...

GPTZero

LLM Engineer (GenAI, NYC)

New York, NY · On-site

$150K - $230K/yr

The ideal candidate is someone who is adept at creating reliable AI agents, prompt engineering ... review stage by marking when candidates met certain key criteria. These tools are never the final ...

Collate

AI Research Scientist

San Francisco, CA · On-site +1

$150K - $350K/yr

What You'll DoExplore new LLM prompt optimization, robustness of LLM applications and modeling ... reviewing applications, analyzing resumes, or assessing responses. These tools assist our ...

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How much do llm prompt review jobs pay per hour?

As of Jun 11, 2026, the average hourly pay for llm prompt review in the United States is $60.90, according to ZipRecruiter salary data. Most workers in this role earn between $54.09 and $69.71 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals in LLM Prompt Review roles, and how can they be managed?

Professionals in LLM Prompt Review roles often encounter challenges such as ensuring prompt clarity, mitigating bias, and maintaining consistency across large volumes of prompts. Balancing creativity with precision is essential, as even small changes can significantly impact model outputs. To manage these challenges, reviewers typically rely on established guidelines, peer collaboration, regular calibration sessions, and continuous feedback from model performance metrics. Staying updated on best practices and working closely with data scientists and prompt engineers also helps maintain high-quality outputs.

What is an LLM Prompt Reviewer?

An LLM Prompt Reviewer is a professional responsible for evaluating, refining, and optimizing prompts used with large language models (LLMs) like GPT-4. Their main goal is to ensure that prompts elicit accurate, useful, and safe responses from the AI. This role involves understanding both the technical and linguistic aspects of prompts, testing various phrasings, and documenting best practices. LLM Prompt Reviewers often collaborate with data scientists, AI trainers, and product teams to improve prompt quality and user experience.

What is the difference between Llm Prompt Review vs Data Annotator?

AspectLlm Prompt ReviewData Annotator
CredentialsBasic understanding of AI and NLP conceptsTypically high school diploma or equivalent, sometimes specialized training
Work EnvironmentRemote or office-based, focused on AI projectsRemote or on-site, working with datasets and labeling tools
Industry UsageUsed in AI development, NLP, and machine learning projectsUsed across various industries for data preparation and labeling
Search & Comparison IntentUnderstanding roles related to AI prompt evaluationComparing data labeling and annotation roles

While both roles involve working with data and AI, Llm Prompt Review focuses on evaluating and refining AI prompts, whereas Data Annotator involves labeling data for machine learning models. The roles differ mainly in their specific tasks and required skills, but both are essential in AI development workflows.

What are the key skills and qualifications needed to thrive as an LLM Prompt Reviewer, and why are they important?

To thrive as an LLM Prompt Reviewer, you need a strong background in linguistics, critical thinking, and AI language model behavior, often supported by experience in content moderation or NLP. Familiarity with prompt engineering tools, annotation platforms, and basic understanding of large language model systems is typically required. Attention to detail, analytical skills, and clear written communication make someone stand out in this position. These skills ensure the creation and evaluation of high-quality prompts that drive accurate, safe, and useful AI model outputs.
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Llm Prompt Review jobs near you

LLM Engineer

Diablo Convoy

Houston, TX • On-site

$120K - $130K/yr

Full-time

Posted 3 days ago

Job description

Overview: 
We are seeking a detail-oriented  LLM Automation Engineer to support AI-driven data analysis, document processing, automation workflows, and reporting initiatives. This role focuses on using artificial intelligence tools, prompt engineering techniques, and structured workflows to analyze large volumes of unstructured data and produce accurate, actionable outputs.
This position is ideal for candidates early in their careers with hands-on experience using AI tools and a strong interest in automation, analytics, and AI-assisted reporting.

Key Responsibilities: 
  • Use AI tools and large language models (LLMs) to summarize, classify, and analyze unstructured documents
  • Apply prompt engineering techniques to generate consistent, repeatable AI outputs
  • Assist in building and maintaining AI automation workflows for reporting and analysis
  • Review, validate, and refine AI-generated content to ensure accuracy and data integrity
  • Support creation of AI-generated visual content, diagrams, and concept imagery
  • Assist with AI-supported floor plan, layout, or spatial analysis projects
  • Collaborate with cross-functional teams to support AI-powered reporting needs
  • Document workflows, prompts, and processes for repeatable use and continuous improvement

Required Qualifications (Must-Have): 
  • Foundational knowledge of artificial intelligence, machine learning concepts, and AI tools
  • Hands-on experience using AI for document analysis, text summarization, and data extraction
  • Basic understanding of prompt engineering and structured prompting techniques
  • Strong written communication, analytical skills, and attention to detail
  • Ability to review AI outputs for quality assurance and make necessary adjustments
  • Strong organizational skills and ability to follow defined workflows
  • Technical/MLTools: Python, Hugging Face, Langchain, RAG, AWS
  • PowerPoint presentation skills