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Generative Ai Prompt Engineer Jobs (NOW HIRING)

XPath Solutions

Generative AI Engineer

Charlotte, NC

$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 ...

New

RapidIT, Inc

AI Architect

Manhattan, NY · On-site

$69.50 - $91.50/hr

Agent AI, Prompt Engineering, Generative AI : AI Product & Copilot Agent Specialist We are seeking a highly technical and innovative professional with deep expertise in Generative AI, Microsoft 365 ...

New

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 ...

Steampunk

Prompt Engineer

Mclean, VA

$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 ...

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 ...

HTC Global Services

AI Engineer

Iselin, NJ · On-site

This role focuses on Generative AI, Large Language Models (LLMs), Prompt Engineering, Agentic AI systems, Machine Learning, Data Science, and AWS-based cloud engineering. The ideal candidate will ...

Saransh Inc

Generative AI Architect

Charlotte, NC · On-site

$61.50 - $81/hr

Generative AI Architect Location: Charlotte, NC (Onsite from Day 1) Job Type: Contract Skill ... and prompt engineering frameworks 3. Participate in cross-functional GenAI initiatives and PoC ...

Symhas

Generative AI Lead

Pleasanton, CA · On-site

$185K/yr

Generative AI Lead We are hiring a Generative AI Lead to spearhead AI innovation at our Pleasanton ... Oversee prompt engineering, fine-tuning, RLHF, and model evaluation practices * Build responsible ...

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Generative Ai Prompt Engineer information

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$81K

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$181K

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

As of Jul 18, 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.

How much do AI prompt engineers get paid?

AI prompt engineers typically earn between $80,000 and $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and natural language processing can command higher salaries, especially in tech hubs or large organizations.

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.

Are AI prompt engineers in demand?

AI prompt engineers are increasingly in demand as organizations seek to optimize interactions with generative AI models. The role requires skills in natural language processing, prompt design, and familiarity with AI tools like GPT, with job growth driven by expanding AI applications across industries.

What engineer makes $500,000 a year?

Highly experienced generative AI prompt engineers working in top tech companies or specialized consulting firms can earn salaries approaching or exceeding $500,000 annually, especially with bonuses and stock options. These roles typically require advanced skills in AI, machine learning, and prompt engineering, along with a strong portfolio of successful projects.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior AI researcher, machine learning director, or AI startup founder, with compensation including salary, bonuses, and equity reaching that amount annually. These roles often require advanced expertise in AI algorithms, programming skills, and experience managing large projects or teams.

What are Generative AI Prompt Engineers?

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.
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Generative Ai Prompt Engineer jobs near you

Generative AI Engineer

XPath Solutions

Charlotte, NC

$60 - $72/hr

Full-time

Posted 2 days ago

New

Job description

Generative AI Engineer
Location

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
  • Vision Language Models (Vision LLMs)
  • Multimodal AI applications
AI Engineering
  • 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
    • MCP (Model Context Protocol)
    • 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
AI / Machine Learning
  • Solid experience with AI/ML frameworks including:
    • PyTorch
    • TensorFlow
Agentic AI

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

  • Session management
  • Memory handling
  • MCP (Model Context Protocol)
  • Tool integration and orchestration
Large Language Models

Practical experience with:

  • Large Language Models (LLMs)
  • Vision Language Models (Vision LLMs / VLMs)
  • Transformer architectures
  • Hugging Face ecosystem
  • vLLM for optimized LLM serving and inference
Retrieval & Search

Experience with:

  • Vector databases
  • Embeddings
  • Retrieval-Augmented Generation (RAG)
  • Semantic Search
Cloud AI Platforms

Experience with one or more:

  • AWS SageMaker
  • Azure OpenAI
  • Google Vertex AI
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:
    • Bias mitigation
    • 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