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Prompt Jobs in Kentucky (NOW HIRING)

Builds with LLMs, AI agents, prompt engineering and developer AI tools (e.g., GitHub Copilot); focused on applied generative AI in production. About the Role The Applied AI Engineer will design ...

$171K - $180K/yr

Explicitly requires vibe coding and hands-on AI/LLM work to build agentic prototypes and automation; strong focus on prompt engineering and rapid prototyping with firm-approved AI tools. About the ...

The Sales Coach designs and deploys AI-powered tools, prompt frameworks, and sales assets using platforms such as Claude, and coaches client sales teams to integrate AI into their day-to-day selling ...

$77K - $105K/yr

Implement CI/CD for AI artifacts, prompt/model versioning, and automated evaluation. * Partner with data engineering to keep Fabric/One Lake data AI-ready. * Risk Management & Guardrails Implement ...

The Sales Coach designs and deploys AI-powered tools, prompt frameworks, and sales assets using platforms such as Claude, and coaches client sales teams to integrate AI into their day-to-day selling ...

You will help establish a disciplined prompt lifecycle (design → test → refine → version) and enable end-users through guidance, examples, and adoption assets. Success requires a strong ability ...

Deep knowledge of ChatGPT capabilities including prompt engineering, conversational AI interaction, content generation, code assistance, data analysis, creative writing applications, API integration ...

Test for jailbreaks, prompt injection, system-prompt and tool leakage, sensitive-data and context leakage, unsafe outputs, policy bypass, tool misuse, excessive agency, resource and token-cost abuse ...

AI Prompt Engineering * Global Regulations Familiarity ATS Optimization KeywordsHard Skills * Supply Chain Risk Screening * Trade Compliance * Export Controls * Sanctions Analysis * AI Prompt ...

Deep knowledge of ChatGPT capabilities including prompt engineering, conversational AI interaction, content generation, code assistance, data analysis, creative writing applications, API integration ...

Ability to explain effective prompt patterns, code review practices for AI output, and rapid prototyping workflows while preparing students for modern AI-augmented development. * Conceptual Teaching ...

Explicitly requires Vibe Coding and AI-assisted engineering practices, using agentic workflows and prompt design to accelerate development while enforcing verification of AI outputs. About the Role ...

Provide friendly, attentive and prompt customer service to members * Fulfill member requests for food and beverages in a high energy, family-friendly environment * Opening and Closing the bar area

Ability to explain effective prompt patterns, code review practices for AI output, and rapid prototyping workflows while preparing students for modern AI-augmented development. * Conceptual Teaching ...

Provide friendly, attentive and prompt customer service to members * Fulfill member requests for food and beverages in a high energy, family-friendly environment * Opening and Closing the bar area

$44.25 - $57.50/hr

Implement responsible AI practices, prompt engineering strategies, guardrails, and model evaluation techniques. * Active Top Secret Clearance * 5+ years of software development experience. * 2+ years ...

The ideal candidate possesses a strong understanding of legal workflows and demonstrates the ability to structure complex legal processes into decision trees, workflow logic, prompt architectures ...

Supervises and directs the activities of Claims Representatives in the investigation and settlement of claims to assure prompt, efficient and fair claims services. MAJOR DUTIES & RESPONSIBILITIES:

$77K - $105K/yr

LLMOps / MLOps: - Establish LLMOps practices including prompt/version management, evaluation suites for quality, safety, bias, and hallucination, and offline/online experiments such as A/B tests ...

Showing results 21-40

Prompt information

See Kentucky salary details

$8

$14

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How much do prompt jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for prompt in Kentucky is $14.32, according to ZipRecruiter salary data. Most workers in this role earn between $12.55 and $15.05 per hour, depending on experience, location, and employer.

What is a prompt engineer?

Prompt engineers are professionals who specialize in designing, refining, and optimizing prompts for artificial intelligence models, particularly large language models like ChatGPT. Their work involves crafting queries that elicit accurate, relevant, and useful responses from AI systems. Prompt engineers often collaborate with developers, data scientists, and product teams to improve AI interactions, troubleshoot issues, and enhance user experience. As AI technology evolves, prompt engineering is becoming an increasingly important skill for leveraging the full potential of language models.

What skills and qualifications are needed to thrive as a prompt engineer?

To thrive as a Prompt Engineer, you need strong skills in natural language processing, programming (often Python), and a solid understanding of AI/ML concepts, typically supported by a degree in computer science or a related field. Familiarity with tools like OpenAI's API, prompt-tuning frameworks, and version control systems such as Git is commonly required. Excellent problem-solving, creativity, and clear communication help you design effective prompts and collaborate with cross-functional teams. These skills and qualities are crucial for optimizing AI model performance and delivering innovative solutions for complex tasks.

What are common challenges faced by prompt engineers when developing effective prompts for AI models?

Prompt Engineers often encounter challenges such as ensuring prompts are clear, unbiased, and consistently produce accurate outputs across various scenarios. Balancing specificity and flexibility in prompts to achieve reliable results can be complex, especially when working with evolving AI models. Collaborating closely with data scientists, product managers, and end users is crucial to iteratively test and refine prompts, making adaptability and strong communication vital skills in this role.

What is the difference between Prompt vs Data Analyst?

AspectPrompt
Required CredentialsTypically no formal credentials; familiarity with AI and NLP tools
Work EnvironmentTech companies, AI labs, remote or office settings
Industry UsageAI development, content creation, chatbot design
Common Search IntentUnderstanding AI prompt engineering and optimization

While Prompt specialists focus on designing inputs for AI models, Data Analysts interpret data to inform decisions. Both roles require analytical skills, but Prompt roles emphasize AI interaction, whereas Data Analysts work with structured data analysis.

What are popular job titles related to Prompt jobs in Kentucky?

For Prompt jobs in Kentucky, the most frequently searched job titles are:

Infographic showing various Prompt job openings in Kentucky as of August 2026, with employment types broken down into 75% Full Time, 17% Part Time, 7% Temporary, and 1% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $29,783 per year, or $14.3 per hour.

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Posted 11 days ago


Job description

Builds with LLMs, AI agents, prompt engineering and developer AI tools (e.g., GitHub Copilot); focused on applied generative AI in production.

About the Role

The Applied AI Engineer will design, build, and scale production AI solutions and agentic workflows using LLMs and cloud-native architectures to automate underwriting and enterprise processes. The role focuses on integrating models, vector databases, and enterprise systems while establishing engineering best practices, governance, and operational monitoring across business functions.

Job DescriptionRole

The Applied AI Engineer will design, implement, and scale Mission’s enterprise AI platform and intelligent automation capabilities. This hands-on engineering role delivers production-ready AI applications, agentic workflows, and integrations that enable AI-powered experiences across underwriting, operations, finance, HR, and other enterprise functions.

Key Responsibilities
  • Design, develop, and deploy production-grade AI solutions using LLMs, AI agents, memory/context management patterns, and machine learning techniques.
  • Build intelligent workflows and AI-powered applications to automate business processes across underwriting, operations, finance, and other functions.
  • Develop and maintain scalable AI services using cloud-native architectures and optimize inference pipelines and orchestration for availability and cost efficiency.
  • Integrate AI capabilities with enterprise platforms (policy administration, submission management, data platforms, document management, external data providers).
  • Design and implement prompt engineering, orchestration frameworks, vector database integrations, and knowledge retrieval solutions.
  • Evaluate, fine-tune, and optimize foundation models and AI workflows for accuracy, latency, scalability, and cost.
  • Develop evaluation frameworks, automated testing, monitoring, and observability to measure model quality, hallucination rates, and system performance.
  • Implement AI guardrails, security controls, governance standards, and Responsible AI practices.
  • Build reusable AI components, SDKs, and engineering frameworks to accelerate delivery of enterprise capabilities.
  • Support production AI systems through monitoring, troubleshooting, and continuous improvement.
Technical Environment (examples cited)
  • Models and providers referenced: Anthropic, OpenAI
  • Developer/augmentation tools: GitHub Copilot, Claude Code, Codex
  • Datastores and platforms referenced: MongoDB, Databricks, SQL Server, vector databases
  • Cloud and infra: AWS, Azure, Google Cloud Platform, CI/CD, Infrastructure as Code
Requirements
  • 3+ years in software engineering, AI engineering, machine learning, or a related technical field, including at least 2 years designing and delivering production AI solutions.
  • Hands-on experience with LLMs, AI memory/context management, AI agents, prompt engineering, and orchestration frameworks.
  • Experience deploying applied AI features and cloud-native technologies.
  • Experience integrating AI solutions with enterprise systems via REST APIs, event-driven patterns, vector DBs, and knowledge repositories.
  • Familiarity with AI evaluation, monitoring, observability, testing frameworks, and Responsible AI principles (security, governance, prompt safety, access controls).
  • Experience with Git, GitLab/GitHub, CI/CD pipelines, Infrastructure as Code, and DevOps/MLOps practices.
  • Experience with Databricks, SQL Server, or other enterprise data platforms.
  • Experience with AWS, Azure, or Google Cloud Platform.
  • Bachelor’s degree in Computer Science, Software Engineering, or equivalent experience.
  • Ability to translate complex business problems into scalable, secure, production-ready AI solutions and collaborate cross-functionally.
Preferred Qualifications
  • Experience developing AI solutions for property & casualty insurance (underwriting, submissions, policy administration).
  • Familiarity with Model Context Protocol (MCP), enterprise AI agents, multi-agent systems, and modern AI engineering platforms.
  • Strong communication skills and cross-functional collaboration experience.
  • Ability to travel up to 10% annually.
  • Remote-first work environment (US-based)
  • Medical, dental, and vision
  • 401(k) and 401(k) match
  • Life and disability benefits
  • Unaccrued paid time off
  • 11 paid holidays
  • Employee assistance program
  • Educational assistance program
  • Employee referral program
  • Paid parental leave
Working Conditions & Location
  • Remote position; occasional planned in-office activities (typically 2–4 times per year). Must reside in the United States and be authorized to work in the U.S. without sponsorship.
  • Standard office ergonomics: extended computer work, regular use of hands, frequent talking/hearing, and normal vision requirements.
Skills

Prompt Engineering AI Engineering Machine Learning Cloud-native Architecture DevOps/MLOps API Development Microservices Event-driven Architecture Vector Database Integration Data Platform Integration Monitoring & Observability Security & Governance Responsible AI Model Evaluation & Testing Collaboration Communication Scalability & Performance Optimization Software Development

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