ZipRecruiter

Log In

1

Generative Ai Developer Jobs in Monroe, NC (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 seeking a highly skilled Generative AI Engineer with a strong Python background to design, develop, and ...

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 ...

USM

JB061726 - AI Developer

Charlotte, NC · On-site

Skills AI Developer Visa Types Green Card, US Citiz.. Title: AI Developer Job Type: Contract ... The ideal candidate will have experience with machine learning, generative AI, and software ...

ICONMA

Agentic AI Developer

Charlotte, NC · On-site

Required : • 3-8 years of experience in software development or data engineering • Hands-on experience in Generative AI or LLM-based applications • Experience building APIs, microservices, or ...

Scout Motors

Lead, AI Engineering

Charlotte, NC

$100K - $131K/yr

The team combines expertise in machine learning, generative AI, data engineering, and platform infrastructure to deliver innovative solutions that improve business outcomes and accelerate digital ...

Compunnel

.Net AI Developer

Charlotte, NC · On-site

NET Developer with AI/ML expertise to design, develop, and implement intelligent applications using ... or generative AI. Hands-on experience with tools/frameworks like: ML.NET. Azure OpenAI / OpenAI ...

next page

Showing results 1-20

All JobsGenerative Ai Developer JobsGenerative Ai Developer Jobs in Monroe, NC

Generative Ai Developer information

See Monroe, NC salary details

$17

$41

$93

How much do generative ai developer jobs pay per hour?

As of Jul 29, 2026, the average hourly pay for generative ai developer in Monroe, NC is $41.99, according to ZipRecruiter salary data. Most workers in this role earn between $21.83 and $50.82 per hour, depending on experience, location, and employer.

What are some common challenges faced by Generative AI Developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What are the key skills and qualifications needed to thrive as a Generative AI Developer, and why are they important?

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

Is generative AI a good career?

Generative AI is a rapidly growing field with high demand for skilled developers who can create and optimize AI models using tools like deep learning frameworks. Careers in this area often require knowledge of machine learning, programming, and data handling, offering opportunities in tech companies, research, and startups. The field provides competitive salaries and continuous learning opportunities due to its evolving nature.

What is the difference between Generative Ai Developer vs Machine Learning Engineer?

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

What is the salary of a generative AI developer?

The salary of a generative AI developer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and skill set. Senior developers with expertise in machine learning frameworks and deep learning may earn higher compensation, especially in tech hubs or companies with advanced AI projects.

What does a generative AI developer do?

A generative AI developer designs and builds algorithms that enable machines to create content such as text, images, or audio. They work with machine learning frameworks, train models on large datasets, and optimize algorithms for performance and accuracy, often using tools like Python and TensorFlow or PyTorch.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence development, such as a senior Generative AI Developer or AI research lead, often involving advanced skills in machine learning, deep learning, and large language models. These roles usually require extensive experience, specialized knowledge, and may include responsibilities like designing AI systems, managing teams, or overseeing AI strategy in organizations with competitive compensation packages. Such salaries are common in top tech companies or specialized AI firms for highly skilled professionals.

What is a Generative AI Developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.
What job categories do people searching Generative Ai Developer jobs in Monroe, NC look for? The top searched job categories for Generative Ai Developer jobs in Monroe, NC are:
What cities near Monroe, NC are hiring for Generative Ai Developer jobs? Cities near Monroe, NC with the most Generative Ai Developer job openings:
Generative Ai Developer jobs near you
Infographic showing various Generative Ai Developer job openings in Monroe, NC as of July 2026, with employment types broken down into 64% Full Time, 25% Part Time, and 11% Contract. Highlights an 59% Physical, 3% Hybrid, and 38% Remote job distribution, with an average salary of $87,334 per year, or $42 per hour.

Generative AI Engineer

XPath Solutions

Charlotte, NC

$60 - $72/hr

Full-time

Posted 13 days ago

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