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Online Generative Ai Engineer Jobs (NOW HIRING)

Aroha Technologies

Generative AI Engineer

Dallas, TX · Hybrid

Generative AI Engineer Location: Dallas, TX (Onsite 5 days/week) Employment Type: Contract Role Overview We are seeking a skilled Generative AI Engineer to design, develop, and deploy enterprise ...

New

Carlin Shayn Inc

Generative AI Engineer

Phoenix, AZ

Generative AI Engineer (Agentic AI / LLM Solutions) Location: Phoenix, AZ / New York City, NY (Hybrid/Onsite) Duration: 12+ Months Contract Interview Mode: Video Interview Position Overview We are ...

Prosum Inc.

Generative AI Engineer

Fort Worth, TX · On-site

$120K - $170K/yr

Generative AI Engineer Location: Remote (U.S.) Salary Range: $120k to $170k About the Role We are seeking a highly skilled Generative AI Engineer to lead the end-to-end delivery of production-grade ...

Prophecy Technologies

Generative AI Engineer

Tampa, FL · On-site

The role is for an AI Engineer focused on designing, developing, and implementing machine learning and AI models, particularly Generative AI applications and Agentic AI solutions. The engineer will ...

OpenDataJobs

Senior Generative AI Engineer

Potomac, MD · On-site +1

$57.25 - $73.75/hr

Our client is seeking a Senior Generative AI Engineer to drive internal initiatives and provide AI engineering support for a major federal agency. The role centers on developing cloud-native ...

OpenDataJobs

Senior Generative AI Engineer

Potomac, MD · Remote

$56.50 - $73/hr

Our client is seeking a Senior Generative AI Engineer to drive internal initiatives and provide AI engineering support for a major federal agency. The role centers on developing cloud-native ...

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Online Generative Ai Engineer information

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$38K

$115.9K

$191.5K

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

As of Jun 12, 2026, the average yearly pay for online generative ai engineer in the United States is $115,864.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,000.00 and $151,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Online Generative AI Engineer, and why are they important?

To thrive as an Online Generative AI Engineer, you need expertise in machine learning, deep learning, and programming languages such as Python, along with a degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (e.g., AWS, GCP), and experience with generative models such as GANs or transformers are typically required. Strong problem-solving abilities, creativity, and effective communication skills help engineers design innovative solutions and collaborate with multidisciplinary teams. These skills and qualities are vital for building robust AI systems that meet user needs and drive technological advancement.

What is an Online Generative AI Engineer?

An Online Generative AI Engineer is a specialized software engineer who designs, develops, and deploys artificial intelligence (AI) models that generate new content, such as text, images, or audio, through online platforms or cloud services. They work with cutting-edge generative models like GPT, DALL-E, or diffusion models, and are responsible for integrating these technologies into web applications or online services. Their role often includes building scalable APIs, optimizing models for real-time usage, and ensuring responsible and ethical AI deployment. These engineers typically collaborate with data scientists, product managers, and UX/UI designers to deliver innovative AI-powered user experiences.

How does an Online Generative AI Engineer typically collaborate with cross-functional teams during model development and deployment?

As an Online Generative AI Engineer, you will regularly work with data scientists, product managers, and software engineers to design, train, and deploy AI models. Collaboration often involves participating in sprint meetings, discussing data requirements, integrating models into production systems, and troubleshooting deployment issues. Effective communication is essential, as you'll need to translate complex model behaviors into actionable insights for non-technical stakeholders, and work closely with DevOps teams to ensure reliable and scalable deployment of generative AI solutions.

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

AspectOnline Generative Ai EngineerData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; experience with machine learning and AI frameworksDegree in Statistics, Data Science, or related fields; proficiency in programming and statistical analysis
Work EnvironmentTech companies, AI startups, research labs; focus on developing AI models and algorithmsBusiness analytics, research, and data analysis teams; focus on data interpretation and insights
Employer & Industry UsagePrimarily in AI development, tech industry, and research institutionsAcross industries like finance, healthcare, marketing, and tech for data-driven decision making

Online Generative Ai Engineers focus on creating and optimizing AI models that generate content, while Data Scientists analyze data to extract insights. Both roles require strong technical skills, but their primary functions differ in application and industry focus.

More about Online Generative Ai Engineer jobs
What cities are hiring for Online Generative Ai Engineer jobs? Cities with the most Online Generative Ai Engineer job openings:
What are the most commonly searched types of Generative Ai Engineer jobs? The most popular types of Generative Ai Engineer jobs are:
What states have the most Online Generative Ai Engineer jobs? States with the most job openings for Online Generative Ai Engineer jobs include:
What job categories do people searching Online Generative Ai Engineer jobs look for? The top searched job categories for Online Generative Ai Engineer jobs are:
Online Generative Ai Engineer jobs near you
Infographic showing various Online Generative Ai Engineer job openings in the United States as of June 2026, with employment types broken down into 63% Full Time, and 37% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $115,864 per year, or $55.7 per hour.
Generative AI Engineer

Generative AI Engineer

Aroha Technologies

Dallas, TX • Hybrid

Other

Posted yesterday

Job description

Job Title: Generative AI Engineer
Location: Dallas, TX (Onsite 5 days/week)
Employment Type: Contract
Role Overview
We are seeking a skilled Generative AI Engineer to design, develop, and deploy enterprise-grade AI solutions using LLMs, RAG pipelines, and agentic AI systems. The ideal candidate will have hands-on experience with modern GenAI frameworks, cloud platforms, and strong software engineering fundamentals.
Key Responsibilities
  • Design and develop Generative AI applications using LLMs (OpenAI, Gemini, Claude, Llama, etc.)
  • Build and optimize RAG (Retrieval-Augmented Generation) pipelines integrating enterprise data
  • Develop AI agents / agentic systems for autonomous workflows and decision-making
  • Implement prompt engineering, embeddings, and vector search solutions
  • Build scalable APIs and microservices for AI-powered applications
  • Integrate AI models with enterprise systems (databases, APIs, data lakes)
  • Deploy solutions on AWS / Azure / Google Cloud Platform with CI/CD pipelines
  • Implement LLMOps/MLOps practices including monitoring, evaluation, and versioning
  • Ensure AI safety, governance, and hallucination mitigation
  • Collaborate with stakeholders to translate business requirements into AI solutions
Required Skills
  • Strong programming experience in Python (mandatory)
  • Hands-on experience with:
    • LangChain / LlamaIndex / Agent frameworks
    • Vector DBs (Pinecone, FAISS, Weaviate, ChromaDB)
    • RAG & embeddings
  • Knowledge of LLMs, NLP, and transformer models
  • Experience with Docker, APIs, and microservices architecture
  • Cloud experience: AWS / Azure / Google Cloud Platform
  • Understanding of MLOps / LLMOps (CI/CD, monitoring, evaluation)
Preferred Qualifications
  • Experience building production-grade GenAI or agentic systems
  • Knowledge of GraphRAG, knowledge graphs, ontology extraction
  • Exposure to Databricks / MLflow / Spark
  • Experience in fine-tuning LLMs or model optimization
Education
  • Bachelor's or Master's degree in Computer Science, AI, ML, or related field
Mandatory / Preferred Certifications (AI-Focused)
Include at least 1 2 of the following:
  • Google Cloud Professional Machine Learning Engineer
  • Microsoft Azure AI Engineer Associate
  • AWS Machine Learning Specialty
  • Databricks Generative AI Engineer Certification
  • NVIDIA Deep Learning Institute (DLI) Certifications
  • OpenAI / LLM / Prompt Engineering certifications (any recognized program)
(Certifications significantly strengthen candidacy for enterprise AI roles.)
Experience
  • 5+ years in software engineering / AI/ML
  • 2+ years in Generative AI / LLM-based solutions
Nice to Have
  • Experience with agentic AI / multi-agent systems
  • Strong understanding of AI governance & responsible AI
  • Prior experience working in onsite enterprise environments

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