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Llm Prompt Review Jobs (NOW HIRING)

JP Morgan Chase

CCB Risk Program Associate

Wilmington, DE · On-site

$57K - $57K/yr

... review to deployment and operational use. Basic Qualifications * Ph.D. or Master's degree from a ... LLM prompt engineering. * Hands-on experience with LLM APIs, Python libraries like Pandas, NumPy ...

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 ... We use AI-based tools to help us to accelerate candidates at the resume review stage by marking ...

Bishop Fox

Senior AI/LLM Penetration Tester

OR · On-site +1

Prompt injection * Jailbreak techniques * Indirect prompt injection * Data leakage and sensitive ... Experience reviewing AI application architectures and identifying security weaknesses across APIs ...

Bishop Fox

Senior AI/LLM Penetration Tester

Prompt injection * Jailbreak techniques * Indirect prompt injection * Data leakage and sensitive ... Experience reviewing AI application architectures and identifying security weaknesses across APIs ...

JPMorgan Chase & Co

CCB Risk Program Associate

Wilmington, DE · On-site

$57K - $57K/yr

... review to deployment and operational use. Basic Qualifications * Ph.D. or Master's degree from a ... LLM prompt engineering. * Hands-on experience with LLM APIs, Python libraries like Pandas, NumPy ...

Collate

AI Research Scientist

San Francisco, CA · On-site +1

What You'll DoExplore new LLM prompt optimization, robustness of LLM applications and modeling ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Collate

AI Research Scientist

San Francisco, CA · On-site

What You'll DoExplore new LLM prompt optimization, robustness of LLM applications and modeling ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Collate

AI Research Scientist

San Francisco, CA · On-site +1

What You'll DoExplore new LLM prompt optimization, robustness of LLM applications and modeling ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

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Llm Prompt Review information

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How much do llm prompt review jobs pay per hour?

As of Aug 13, 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
Infographic showing various Llm Prompt Review job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $126,666 per year, or $60.9 per hour.

Full Stack Developer with Documentum (AI/LLM Expertise)

Kanak Elite Services Inc

Reston, VA • On-site

Contractor

Re-posted 7 days ago

Job description

Hello There,

Wish you a Happy Thursday,

My name is Yashmita, and I am a Technical Recruiter at Kanak IT Services LLC. I am reaching out to you regarding the following job opportunity. If you are interested, kindly reply to this email yashmita@kanakits.com with your updated resume.  

NOW HIRING: FULL STACK DEVELOPER WITH DOCUMENTUM (AI/LLM EXPERTISE)

LOCATION: RESTON, VA (LOCALS ONLY)

We’re seeking an experienced Full Stack Developer with deep expertise in AI (Artificial Intelligence), LLM (Large Language Models), and ECM (Enterprise Content Management) — preferably with hands-on experience in Documentum.

The ideal candidate will bring a strong background in Java, Python, modern front-end frameworks, and AWS, along with a solid understanding of software architecture, APIs, and ECM integrations.

Key Responsibilities:

  • Design, develop, and deploy full-stack applications using Java, Python, and React/Angular.
  • Integrate and enhance Enterprise Content Management (ECM) platforms — preferably Documentum.
  • Develop and integrate RESTful APIs using Java/Spring frameworks.
  • Work with LLM models — evaluate, fine-tune, and integrate with ECM systems.
  • Implement prompt engineering, data preprocessing, and AI/ML-based content solutions.
  • Collaborate with cross-functional teams to ensure scalable, secure, and efficient software delivery.
  • Manage CI/CD pipelines and development tools (Git, Jenkins, Jira, IntelliJ, Tomcat/J2EE).
  • Work within Agile/Scrum practices, participating in sprint planning, reviews, and retrospectives.
  • Leverage AWS cloud services (EC2, ECS, RDS, SQS, SNS, Lambda, Textract, Bedrock).
  • Conduct performance testing, code reviews, and implement DevSecOps best practices.

Required Skills & Experience:

  • 7+ years of experience in full-stack development.
  • Strong proficiency in Java and Python.
  • Front-end development with React or Angular.
  • Hands-on with Documentum or similar ECM systems.
  • Deep understanding of REST APIs, Spring Boot, and microservices architecture.
  • Experience with data modeling, PostgreSQL, MongoDB, or DynamoDB.
  • Experience with AWS Cloud (3+ years) — EC2, ECS, RDS, SQS, SNS, Lambda, etc.
  • Working knowledge of LLM models, prompt engineering, and AI data pipelines.
  • Strong grasp of software design patterns, code quality, and security practices.

 Preferred Certifications:

  • AWS Certified Developer or Architect
  • Documentum Certification
  • Java Certification (Oracle or equivalent)