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Generative Ai Instructor Jobs (NOW HIRING)

CMC Global Company Limited.

$110 - $160/hr

* Design and deliver instructor-led AI training programs for engineers, business professionals ... Teach practical applications of Generative AI across software development, manufacturing, supply ...

Nwacc

... instructors to teach foundational courses in Artificial Intelligence as part of the college ... learning, generative AI, data analytics, prompt engineering) * Strong communication and ...

NorthWest Arkansas Community College

... instructors to teach foundational courses in Artificial Intelligence as part of the college ... learning, generative AI, data analytics, prompt engineering) * Strong communication and ...

Axis

AI Enablement Specialist

Chelmsford, MA · On-site

$100/hr

Understanding of generative AI mechanics, including prompt engineering and the ethical implications ... Trainer / instructor experience a pro Physical Demands and Travel: Reasonable accommodations may be ...

Digipen

$67 - $78/hr

Generative AI and Large Language Models * AI for Business Applications * Advanced Topics in AI Research Salary Range $6,048 for positions at the Assistant Professor level. Exceptional experience may ...

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Generative Ai Instructor information

What does a generative AI instructor do?

A Generative AI Instructor is responsible for teaching individuals or groups about generative artificial intelligence technologies, such as machine learning models that create new content (text, images, audio, etc.). They design curriculum, lead workshops, and provide hands-on demonstrations to help students understand how to build, fine-tune, and deploy generative AI models. Additionally, they stay updated on the latest advancements in AI and help learners understand ethical considerations and real-world applications of generative AI.

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

To thrive as a Generative AI Instructor, you need a deep understanding of machine learning, natural language processing, and AI concepts, often supported by a degree in computer science or a related field. Familiarity with tools like Python, TensorFlow, PyTorch, and platforms such as Jupyter Notebook is typically required, along with experience using generative AI frameworks and models. Strong communication, adaptability, and the ability to simplify complex topics for diverse learners are important soft skills in this role. These skills ensure effective teaching, empower students to grasp advanced AI concepts, and keep coursework relevant in a fast-evolving field.

What are some common challenges generative AI instructors face when teaching complex concepts to diverse learners?

Generative AI Instructors often encounter the challenge of breaking down advanced machine learning and artificial intelligence concepts into digestible lessons for students with varying backgrounds. Balancing the technical depth required for industry relevance with accessibility for beginners requires flexible teaching strategies and strong communication skills. Additionally, keeping course materials up-to-date with the rapidly evolving AI landscape is essential, which means instructors must continually learn and adapt their curriculum. Collaboration with peers and industry professionals is common to ensure content accuracy and relevance.

What is the difference between Generative Ai Instructor vs Data Scientist?

AspectGenerative Ai InstructorData Scientist
Required CredentialsAI/ML certifications, teaching experienceStatistics, programming, data analysis degrees
Work EnvironmentEducational settings, online platformsResearch labs, tech companies, finance
Employer & Industry UsageEdTech, training programsTech firms, finance, healthcare

While both roles involve AI expertise, a Generative Ai Instructor primarily focuses on teaching and training others in generative AI techniques, often within educational or training environments. In contrast, a Data Scientist analyzes data to derive insights and build models across various industries. Both roles require strong technical skills, but their core responsibilities and work settings differ significantly.

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Generative Ai Instructor jobs near you
Infographic showing various Generative Ai Instructor job openings in the United States as of August 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 50% In-person, 33% Hybrid, and 17% Remote job distribution.

FDE Instructor - AI Deployment Lead Devin AI

Photon

Charlotte, NC • On-site

Other

Posted 27 days ago

Job description

Job Title: FDE Instructor - AI Deployment Lead Devin AI
Location: Charlotte NC / Concord CA
Duration: Long Term
Job Description:
Responsibilities: We are seeking a highly skilled AI Deployment Lead Devin AI with deep expertise in Devin and modern Generative AI (GenAI) tools to support enterprise-scale rollout and adoption across Line of Business (LOB) engineering teams.
This is a hands-on engineering role focused on enabling LOB teams to improve their product delivery lifecycle through effective utilization of GenAI tools, coupled with a strong ability to train and upskill engineering teams on autonomous development workflows. The ideal candidate combines solid software engineering fundamentals, practical experience integrating GenAI solutions into enterprise development environments, and demonstrated success teaching others to be effective with these tools not just executing tasks independently.
This role requires close partnership with product, platform, security, and engineering teams to accelerate delivery, improve developer productivity, and drive scalable, well-governed adoption of GenAI capabilities across the organization.
Responsibilities
  • Lead the end-to-end rollout and scaling of GenAI tools (Devin, Claude Code, Cursor) across CDXO and LOB engineering teams.
  • Act as a hands-on engineer, building and integrating solutions into enterprise SDLC workflows (CI/CD pipelines, repositories, APIs).
  • Define and execute enterprise-wide rollout strategies, including phased onboarding and scaling models.
  • Partner with LOB teams to enhance the product delivery lifecycle using GenAI capabilities.
  • Design and deliver structured developer onboarding, training, and enablement programs teaching engineering teams to work effectively with autonomous development tools, not simply completing tasks on their behalf.
  • Advise teams on when to apply autonomous (Devin) vs. assistive (Copilot) approaches based on use case and risk profile.
  • Monitor tool adoption, usage metrics, and performance, ensuring continuous optimization.
  • Provide hands-on troubleshooting, performance tuning, and scaling support.
  • Establish reusable playbooks and best practices for enterprise-wide GenAI adoption.
  • Ensure alignment with enterprise governance, security, and compliance frameworks, including secrets/identity management practices for agent-based tooling.
  • Identify adoption gaps and proactively drive improvements in efficiency and scalability.
Requirements
Experience
  • 5 8+ years of software engineering experience, with strong fundamentals in at least one enterprise stack (e.g., Java, Python, or TypeScript/React/Angular).
  • Working knowledge of distributed systems, microservices, event-driven architectures, and API design/integration.
  • Hands-on experience with CI/CD pipelines and developer tooling ecosystems.
  • Familiarity with cloud platforms such as OpenShift (OCP) and Google Cloud Platform (Google Cloud Platform).
  • Demonstrated experience training, mentoring, or enabling engineering teams on new tools or workflows prior instructor, enablement, or forward-deployed engineering experience strongly preferred.
GenAI / LLM Expertise
Hands-on experience with:
  • Devin
  • Claude / Anthropic models
  • Cursor or similar developer productivity tools (Copilot, etc.)
Strong understanding of:
  • Prompt engineering
  • RAG (Retrieval Augmented Generation)
  • Agent-based workflows and tool usage
  • Multi-agent architectures
  • MCP (Model Context Protocol) servers and integrations
  • Agentic systems including orchestration, tool chaining, and autonomous decision-driven workflows
  • Governance & Security
  • Familiarity with enterprise AI governance and responsible-AI frameworks in regulated environments.
  • Working knowledge of secrets management and identity platforms (e.g., CyberArk, HashiCorp Vault) and enterprise IAM/SSO (e.g., Entra ID) as applied to agent identity and access control is a plus.
Preferred
  • Ability to thrive in fast-paced, evolving environments.
  • Strong collaboration skills with cross-functional and LOB teams.
  • Capability to translate business requirements into technical solutions.
  • Experience working in enterprise environments with governance & compliance requirements.
  • Strong passion for driving adoption and improving developer productivity with the patience and communication skills to teach, not just build.

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