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Remote Generative Ai Engineer Jobs (NOW HIRING)

Canada or Mexico (Remote) Job Type: Contract Experience: 5-10 years software development; 2-4 years hands-on Generative AI Shift: 1:00 PM - 9:00 PM PST Job Overview We are seeking an experienced AI ...

You will work closely with product, engineering, and data teams to design intelligent systems ... This is an exciting opportunity for someone passionate about machine learning, generative AI, LLMs ...

AI Engineer - Remote Apply now Job no: 504788 Work type: Full Time Regular Location: Nebraska ... This role calls for a multifaceted expert with deep knowledge of Machine Learning, Generative AI ...

Remote What is in it for you? As a Gen AI Engineer , you will design, develop, and maintain Generative AI solutions that drive intelligent automation and advanced data processing. Responsibilities:

We are hiring an AI Engineer specializing in LLMs (Large Language Models), Retrieval Augmented ... Develop Generative AI solutions, including chatbots, summarization, and content creation tools.

Sr. Gen AI Engineer

$107K - $146K/yr

Remote * Bachelor's or Master's degree in Computer Science, Engineering, AI, or a related field ... Proven experience designing and delivering enterprise-scale AI solutions, including Generative AI ...

Generative AI Engineering Intern (Graduate)

$17.25 - $22.25/hr

Responsibilities Peraton is seeking motivated Generative AI Engineering Interns (Graduate ... This internship provides competitive hourly compensation, flexible and remote-friendly scheduling ...

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Remote Generative Ai Engineer information

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$38K

$115.9K

$191.5K

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

As of Aug 31, 2026, the average yearly pay for remote 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 is a remote generative AI engineer?

A Remote Generative AI Engineer is a technology professional who specializes in developing, training, and deploying artificial intelligence models that can generate new content—such as text, images, audio, or video—while working from a remote location. These engineers typically work with advanced machine learning techniques like deep learning, neural networks, and large language models. Their responsibilities often include designing algorithms, optimizing model performance, and collaborating with distributed teams to build innovative AI-driven solutions. The remote aspect allows them to perform their duties from anywhere with internet access, offering flexibility and access to global opportunities.

What are the key skills and qualifications needed to thrive as a remote generative AI engineer?

To thrive as a Remote Generative AI Engineer, you need a solid background in computer science, machine learning, and deep learning, typically with a relevant degree and experience in building AI models. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (such as AWS or Azure), and version control systems like Git is essential. Strong problem-solving, self-motivation, and effective remote communication set outstanding engineers apart in this role. These skills are crucial for developing innovative AI solutions, collaborating across distributed teams, and delivering impactful results in a remote work environment.

How do remote generative AI engineers typically collaborate with cross-functional teams to deliver AI-driven solutions?

Remote Generative AI Engineers often work closely with data scientists, product managers, and software engineers to integrate generative AI models into products or services. Collaboration is usually facilitated through virtual meetings, code repositories, and project management tools, enabling seamless communication across different time zones. Regular check-ins and sprint reviews help ensure alignment on goals, while documentation and clear communication are essential for maintaining project momentum. This collaborative environment not only fosters innovation but also allows engineers to gain exposure to a variety of perspectives and expertise.

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

AspectRemote Generative Ai EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related; experience with generative modelsBachelor's or higher in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentCollaborates on AI model development, focuses on generative models like GPT, GANsDevelops and deploys ML models for various applications, including predictive analytics
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, and data-driven industries

While both roles involve AI and machine learning, a Remote Generative Ai Engineer specializes in creating models that generate content, such as text or images, using generative techniques. In contrast, a Remote Machine Learning Engineer works on a broader range of ML models for predictive or classification tasks. The roles often overlap but differ in focus and application.

How much does a remote generative AI engineer make?

A remote generative AI engineer typically earns between $100,000 and $160,000 annually, depending on experience, skills, and the company's location. Senior roles or those with specialized expertise in machine learning and deep learning can command higher salaries, especially with proficiency in tools like TensorFlow or PyTorch.

What are the best remote generative AI engineer jobs?

Remote generative AI engineer jobs are available across technology companies, research institutions, and startups, often requiring skills in machine learning frameworks like TensorFlow or PyTorch and experience with natural language processing or computer vision. These roles typically involve developing and deploying AI models remotely, with some positions offering flexible schedules and requiring certifications or advanced degrees in computer science or related fields.

What is the average salary of a remote generative AI engineer?

The average salary for a remote generative AI engineer typically ranges from $100,000 to $150,000 annually, depending on experience, skills in machine learning frameworks, and the complexity of projects. Senior roles or those with specialized expertise in deep learning and large language models can earn higher compensation. Remote positions often offer competitive pay comparable to on-site roles in the tech industry.
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Infographic showing various Remote Generative Ai Engineer job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $115,864 per year, or $55.7 per hour.

Full-time

This job post has expired 4 days ago. Applications are no longer accepted.


Job description

Job Title: AI Engineer - Generative AI
Location: Canada or Mexico (Remote)
Job Type: Contract
Experience: 5-10 years software development; 2-4 years hands-on Generative AI
Shift: 1:00 PM - 9:00 PM PST
Job Overview
We are seeking an experienced AI Engineer specialising in Generative AI to design, develop, and deploy enterprise-grade AI applications powered by Large Language Models (LLMs). The ideal candidate will have hands-on experience building Retrieval-Augmented Generation (RAG) solutions, document intelligence platforms, multimodal AI applications, and scalable AI APIs using Azure OpenAI and Python.
Key Responsibilities
  • Design, develop, and deploy enterprise Generative AI applications using Azure OpenAI Services
  • Build RAG pipelines using embeddings and vector databases
  • Develop scalable REST APIs using FastAPI and Flask
  • Integrate Vision LLMs for image, document, and multimodal understanding
  • Build document processing pipelines using PyMuPDF for PDF extraction and parsing
  • Implement semantic search using FAISS Vector Database
  • Engineer prompts and optimise LLM responses for enterprise use cases
  • Develop AI-powered chatbots, document Q&A, summarisation, and intelligent automation solutions
  • Implement monitoring and evaluation frameworks using Opik or similar LLM observability tools
  • Ensure AI applications follow security, governance, and responsible AI best practices
Required Skills
  • Generative AI: LLMs, Prompt Engineering, RAG, Embeddings, Semantic Search, AI Agents, Function Calling, Model Evaluation
  • Cloud & AI Platforms: Azure OpenAI Service, Azure AI Services, Azure Storage
  • Programming: Python (Advanced), FastAPI, Flask, REST API Development, Async Programming
  • AI Frameworks: LangChain, LlamaIndex, PyMuPDF, FAISS, Vision LLMs, OpenAI SDK
  • Dev Tools: VS Code, PyCharm, Git, GitHub / Azure DevOps, Docker
  • Observability: Opik, LLM Monitoring, Experiment Tracking, Performance Benchmarking
Preferred Skills
  • LangGraph, AutoGen / CrewAI, Azure AI Search, Cosmos DB, PostgreSQL, Redis, Kubernetes, MLflow, Hugging Face, OCR (Azure Document Intelligence, Tesseract), CI/CD pipelines, MLOps, Transformers, Azure Cognitive Search, Azure Functions
Location & Work Model
Fully remote - open to candidates based in Canada or Mexico. Shift: 1:00 PM - 9:00 PM PST (please confirm availability before applying).
Engagement Details
Contract engagement. Duration to be confirmed upon selection.