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Generative Ai Prompt Engineer Jobs (NOW HIRING)

XPath Solutions

NY · On-site

$140 - $210/hr

Key Responsibilities Design and implement Generative AI solutions for: * Text‑based AI ... Develop and optimize advanced prompt engineering strategies to improve LLM performance, accuracy ...

New

XPath Solutions

Generative AI Engineer

Charlotte, NC · On-site

$140 - $190/hr

Key Responsibilities Design and implement Generative AI solutions for: * Text‑based AI ... Develop and optimize advanced prompt engineering strategies to improve LLM performance, accuracy ...

XPath Solutions

Generative AI Engineer

Charlotte, NC · On-site

$60 - $72/hr

Generative AI Engineer Location Dallas, TX or Charlotte, NC or Raleigh, NC Role Overview We are ... Develop and optimize advanced prompt engineering strategies to improve LLM performance, accuracy ...

MDAEdge

Generative AI Engineer

Austin, TX · On-site

... prompt engineering techniques. • Implement few-shot prompting strategies for improved LLM ... Required : • Designed and developed scalable generative AI platforms for enterprise use cases ...

System One

AI Prompt Engineer (IRS MBI Cleared)

Greenbelt, MD · Remote

$104K - $138K/yr

AI Prompt Engineer Location: Greenbelt, Maryland Type: 6 months Contract To Hire Work Model: 100% Remote (EST hours) Security Clearance: Must have an active IRS MBI Clearance Overview System One is ...

System One

AI Prompt Engineer (IRS MBI Cleared)

Greenbelt, MD · Remote

$104K - $138K/yr

AI Prompt Engineer Location: Greenbelt, Maryland Type: 6 months Contract To Hire Work Model: 100% Remote (EST hours) Security Clearance: Must have an active IRS MBI Clearance Overview System One is ...

Steampunk

Prompt Engineer

Mclean, VA

$115K - $140K/yr

We are seeking a Prompt Engineer design, test, and refine interaction patterns for generative AI systems used across our client engagements. This role is central to shaping how users experience AI ...

Steampunk

Prompt Engineer

Mclean, VA · On-site

$115K - $140K/yr

Overview We are seeking a Prompt Engineer design, test, and refine interaction patterns for generative AI systems used across our client engagements. This role is central to shaping how users ...

USM

JB061755 - AI Prompt Engineer - Remote

Advanced Prompt Engineering * Structured Data Transformation, transformation rules, requirements etc. * LLM, LLM instructions * Build and Test AI workflows * AI Experience - Perplexity, ChatGPT or ...

Steampunk

Prompt Engineer

Mclean, VA · On-site

$115K - $140K/yr

Overview We are seeking a Prompt Engineer design, test, and refine interaction patterns for generative AI systems used across our client engagements. This role is central to shaping how users ...

Lares IT Solutions Inc

Generative AI Engineer

Plano, TX · On-site

Generative AI Developer Plano, TX We are seeking a seasoned Generative AI Developer with expertise ... prompt engineering, AI-assisted coding tools (GitHub Copilot) * Languages: Python (scripting & AI ...

SS&C Technologies

Key Responsibilities Generative AI & Prompt Engineering * Design, develop, and optimize applications leveraging internal LLM platforms * Create, test, and maintain high-quality prompts to drive ...

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All JobsGenerative Ai Prompt Engineer Jobs

Generative Ai Prompt Engineer information

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$81K

$106.4K

$181K

How much do generative ai prompt engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for generative ai prompt engineer in the United States is $106,377.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,500.00 and $100,000.00 per year, depending on experience, location, and employer.

What is the difference between Generative Ai Prompt Engineer vs Data Scientist?

AspectGenerative Ai Prompt EngineerData Scientist
Required CredentialsKnowledge of AI models, programming skills, familiarity with NLPDegree in Data Science, Statistics, or related field; programming skills
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, tech industries
Employer & Industry UsageDevelops prompts for AI models, focuses on language generationAnalyzes data, builds models, derives insights

While both roles require programming skills and familiarity with data and AI, Generative Ai Prompt Engineers specialize in crafting prompts to optimize AI language models, whereas Data Scientists focus on analyzing data and building predictive models. The roles often overlap in tech environments but serve different core functions.

What is a generative AI prompt engineer?

Generative AI Prompt Engineers are professionals who design, develop, and refine prompts to optimize the performance of generative AI models, such as large language models or image generators. They work to understand how these models interpret inputs and craft prompts that achieve specific outputs or behaviors. Their work often involves experimentation, data analysis, and collaboration with machine learning teams to improve AI-generated content, ensuring it is accurate, relevant, and aligned with user or business goals.

What are the key skills and qualifications needed to thrive as a generative AI prompt engineer, and why are they important?

To thrive as a Generative AI Prompt Engineer, you need a strong grasp of natural language processing, machine learning concepts, and experience with large language models, often supported by a degree in computer science or a related field. Familiarity with AI development frameworks (such as TensorFlow or PyTorch), prompt engineering tools, and APIs like OpenAI's GPT is typically required. Creative problem-solving, attention to detail, and effective communication are vital soft skills for crafting high-quality prompts and collaborating with interdisciplinary teams. These skills ensure the creation of robust, contextually relevant prompts that drive optimal AI outputs and innovation in conversational AI applications.

What are some common challenges generative AI prompt engineers face when collaborating with cross-functional teams?

Generative AI Prompt Engineers often work closely with data scientists, product managers, and designers to develop, refine, and implement AI-driven solutions. A common challenge in this collaboration is ensuring that prompts are both technically feasible and aligned with user needs or business goals. Effective communication is crucial, as team members may have varying levels of familiarity with prompt engineering concepts. Prompt Engineers must frequently translate technical requirements into actionable tasks and provide clear feedback on what is or isn't possible within current AI model capabilities.
More about Generative Ai Prompt Engineer jobs
What are the most commonly searched types of Generative Ai Prompt Engineer jobs? The most popular types of Generative Ai Prompt Engineer jobs are:
What job categories do people searching Generative Ai Prompt Engineer jobs look for? The top searched job categories for Generative Ai Prompt Engineer jobs are:
Generative Ai Prompt Engineer jobs near you
Infographic showing various Generative Ai Prompt Engineer job openings in the United States as of August 2026, with employment types broken down into 74% Full Time, 22% Part Time, and 4% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $106,377 per year, or $51.1 per hour.

Generative AI Engineer

XPath Solutions

NY • On-site

$140 - $210/hr

Other

Posted 2 days ago

New

Job description

Charlotte, United States | Posted on 07/15/2026

Dallas, TX or Charlotte, NC or Raleigh, NC

Role Overview

We are seeking a highly skilled Generative AI Engineer with a strong Python background to design, develop, and deploy cutting‑edge AI solutions. The ideal candidate will have hands‑on experience with Large Language Models (LLMs), Vision Language Models (Vision LLMs/VLMs), vLLM inference framework, prompt engineering, and modern Generative AI frameworks, along with proven expertise in building scalable AI applications for enterprise use cases.

This role focuses on developing Agentic AI systems, Retrieval‑Augmented Generation (RAG), multimodal AI solutions, and high‑performance LLM inference while integrating GenAI capabilities into production‑grade enterprise applications.

Mission

Design and deliver scalable, production‑ready Generative AI solutions leveraging modern LLMs, Vision LLMs, Agentic AI frameworks, RAG architectures, and cloud AI platforms to power intelligent enterprise applications.

Key Responsibilities Design and implement Generative AI solutions for:
  • Text‑based AI applications
  • Image‑based AI applications
  • Multimodal AI applications
  • Develop and optimize advanced prompt engineering strategies to improve LLM performance, accuracy, and reliability.
  • Build and integrate embedding‑based retrieval systems and Retrieval‑Augmented Generation (RAG) pipelines.
Design and implement Agentic AI applications including:
  • Context management
  • Session and memory handling
  • Tool calling and workflow orchestration
  • Deploy and optimize vLLM for high‑throughput, low‑latency LLM inference in production environments.
  • Build scalable APIs using Python and integrate GenAI capabilities into enterprise applications and workflows.
  • Collaborate with cross‑functional teams to deploy AI solutions at scale.
  • Ensure AI solutions are secure, scalable, reliable, and production‑ready.
Required Qualifications Programming
  • Strong proficiency in Python

Solid experience with AI/ML frameworks including:

  • PyTorch
  • TensorFlow
Agentic AI

Hands‑on experience building multi‑agent AI systems, including:

  • Session management
  • Memory handling
  • Tool integration and orchestration

Practical experience with:

  • vLLM for optimized LLM serving and inference
Retrieval & Search

Experience with:

  • Embeddings
  • Retrieval‑Augmented Generation (RAG)
  • Semantic Search

Experience with one or more:

  • AWS SageMaker
MLOps
  • Understanding of MLOps and LLMOps practices
  • Experience deploying scalable AI applications in production
Preferred Qualifications
  • Experience with multimodal AI systems combining text, images, and documents

Knowledge of AI ethics, including:

  • Responsible AI practices
  • Experience designing AI systems with governance, transparency, and compliance in mind
  • Experience with distributed GPU inference, model optimization, quantization, and high‑performance AI serving
  • Familiarity with frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or AutoGen
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