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Fullstack Academy

Immersive coding bootcamp for software engineering

Instructor - Advanced GenAI

Corporate & Technical TrainingConfirmed live in the last 24 hours
Part-timeRemote in USA$80 /hr

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Engineering, or a related field is required.
  • At least 10 years of professional experience in Artificial Intelligence, Generative AI, Machine Learning, Data Science, Software Engineering, or related domains is required.
  • Hands-on experience designing, developing, implementing, or deploying Generative AI and large language model-powered applications is required.
  • Prior experience delivering online instructor-led training for professionals or adult learners is required.
  • Demonstrated expertise in Generative AI, Large Language Models, Prompt Engineering, Retrieval-Augmented Generation (RAG), AI APIs, and LLM application development is required.
  • Strong understanding of Generative AI and foundation models, LLMs and their architectures and capabilities, Prompt Engineering and advanced prompting techniques, RAG architectures, embeddings and vector databases, semantic search and knowledge retrieval, function calling and tool integration, LLM APIs and integrations, LLM orchestration, context management, fine-tuning and model customisation, LLM evaluation and performance optimisation, hallucination mitigation, multimodal Generative AI, AI-powered automation, and responsible AI, security, privacy, bias, and governance is required.
  • Hands-on experience with Generative AI frameworks and platforms such as OpenAI, Claude, Gemini, Hugging Face, LangChain, LangGraph, LlamaIndex, or similar technologies is required.
  • Strong understanding of AI APIs, LLM integration, and enterprise Generative AI applications is required.
  • Strong hands-on expertise in Advanced Generative AI and LLM application development is required.
  • Instructional and learner engagement abilities are required, including the ability to simplify complex Generative AI and LLM concepts with practical examples and demonstrations.
  • Experience building or demonstrating LLM-powered applications, RAG solutions, AI automation workflows, or Generative AI solutions is required.
  • Strong understanding of Prompt Engineering, RAG, embeddings, vector databases, tool calling, function calling, and LLM orchestration is required.
  • Ability to explain LLM capabilities, limitations, context management, evaluation, and optimisation is required.
  • Strong understanding of Generative AI, Artificial Intelligence, Machine Learning, and modern AI technologies is required.
  • Experience conducting live virtual training using Zoom, Microsoft Teams, or similar platforms is required.
  • Learner engagement, facilitation, Q&A management, and activity-driven learning abilities are required.
  • Ability to connect Generative AI concepts with real-world business use cases is required.
  • Ability to conduct interactive, activity-driven learning experiences is required.
  • Ability to connect Generative AI concepts with real-world business use cases is required.
  • Flexibility for evening and weekend availability is preferred based on learner cohort schedules.
  • Applicants must be legally authorised to work in the United States at the time of application and throughout employment.

Responsibilities

  • Deliver live online instructor-led training sessions covering Advanced Generative AI, Large Language Models, Prompt Engineering, RAG, AI APIs, LLM applications, and AI-powered automation.
  • Teach advanced topics including Generative AI fundamentals and evolution; LLMs and architectures; foundation models and modern LLMs; Prompt Engineering, advanced prompting, structured prompting and prompt optimisation; system prompts and instruction design; RAG; embeddings and semantic search; vector databases and knowledge retrieval; context windows and context management; function calling and tool integration; LLM APIs and application development; orchestration; fine-tuning and model customisation; model evaluation and output quality; hallucination mitigation and factuality; multimodal Generative AI; text, image, audio, and video generation; workflow automation; enterprise applications; AI coding assistants and developer productivity tools; responsible AI, security, privacy, bias, and governance; and emerging technologies and industry trends.
  • Prepare and continuously update training presentations, learning materials, practical exercises, hands-on activities, Generative AI demonstrations, Prompt Engineering exercises, LLM application demonstrations, RAG demonstrations, real-world business case studies, templates, and reference materials.
  • Conduct interactive workshops, Q&A sessions, knowledge checks, guided practice, and hands-on demonstrations.
  • Conduct practical demonstrations using platforms, frameworks, and tools such as ChatGPT, Claude, Gemini, Microsoft Copilot, OpenAI APIs, Anthropic APIs, Google Gemini APIs, Hugging Face, LangChain, LangGraph, LlamaIndex, vector databases, RAG frameworks, AI coding assistants such as GitHub Copilot, Cursor, and Claude Code or similar tools, and workflow automation platforms.
  • Guide learners through real-world Generative AI scenarios using practical business and industry examples.
  • Demonstrate how Generative AI can generate, analyse, transform, summarise, and interact with text, documents, images, audio, video, code, and enterprise data.
  • Demonstrate how LLM applications can integrate with external data sources, APIs, databases, enterprise systems, and business workflows.
  • Support learners in developing practical skills for designing, building, evaluating, and implementing Generative AI solutions.
  • Maintain learner engagement and instructional quality throughout sessions.
  • Stay updated with Generative AI developments, foundation models, LLM technologies, AI tools, frameworks, multimodal AI capabilities, and industry trends.
  • Collaborate with internal curriculum teams to improve training content and learner outcomes.
  • Provide individualised learner support during live training sessions and scheduled office hours.
  • Maintain regular communication about learner progress, training expectations, and skill development.
  • Respond promptly and professionally to learner and internal team communications.
  • Provide timely, constructive feedback on practical exercises, activities, and learning assessments.
  • Support learners in applying Generative AI, LLM, Prompt Engineering, RAG, and AI application development concepts to practical business scenarios.
  • Help learners design and experiment with LLM applications, RAG solutions, AI-powered workflows, and Generative AI use cases through guided practice and hands-on demonstrations.
  • Evaluate learner progress based on participation, knowledge checks, practical exercises, and hands-on activities.
  • Maintain accurate records of learner engagement and performance.
  • Identify learners requiring additional support and collaborate with internal teams to improve learning outcomes.
  • Contribute to continuous improvement initiatives for training quality and learner success.
  • Adhere to institutional policies and instructional standards.
  • Foster an inclusive, collaborative, and professional learning environment.
  • Serve as a mentor and industry role model for learners developing their Generative AI and LLM skills.
  • Collaborate with instructional staff and curriculum teams to enhance learner experience and training effectiveness.
  • Represent Simplilearn professionally when interacting with learners, staff, and external stakeholders.

Desired Qualifications

  • Experience training professionals, working professionals, or adult learners in Advanced Generative AI, LLMs, or AI applications is preferred.
  • Experience creating Generative AI training content, exercises, demonstrations, or case studies is preferred.
  • Hands-on experience developing production-grade LLM applications or enterprise Generative AI solutions is preferred.
  • Experience implementing RAG pipelines, vector databases, embeddings, and knowledge retrieval systems is preferred.
  • Experience integrating LLMs with external APIs, databases, enterprise applications, and business systems is preferred.
  • Experience with multimodal Generative AI applications is preferred.
  • Experience with AI-powered automation and workflow orchestration is preferred.
  • Experience using AI coding assistants such as GitHub Copilot, Cursor, Claude Code, or similar tools is preferred.
  • Experience with Python and AI development environments is preferred.
  • Familiarity with current and emerging foundation models and Generative AI platforms is preferred.
  • Experience demonstrating Generative AI use cases across different business functions is preferred.
  • Strong understanding of responsible AI, AI ethics, security, privacy, bias, and governance is preferred.

About the Company

Fullstack Academy

Immersive coding bootcamp for software engineering

FullStack Academy provides intensive bootcamps to help people transition into tech careers. Its flagship program teaches full-stack JavaScript (Node.js, React, PostgreSQL) through project-based learning, with extensions into cybersecurity, data analytics, and DevOps. The program uses selective admissions and combines hands-on projects with career services like coaching, resume help, and interview prep to boost job outcomes. Now part of Simplilearn, it aims to place graduates into high-paying tech roles by offering practical skills and strong job placement support.

Company size
201-500
Company stage
Acquired
Total funding
$130K
Headquarters
New York City, New York
Founded
2012

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