AI Trainer

•

Company Name:

DAGCHAIN LABS CORPORATION •

Employment Type:

Full Time •

Work Type:

Remote •

Salary:

Negotiable

Job Overview The AI Trainer AI Chatbots, Personal AI and Scope Based AI Agents is a specialist role responsible for training learners to design, build, and deploy intelligent AI chatbots, personal AI assistants, and task focused AI agents. This role focuses on moving beyond basic conversational bots toward goal driven, context aware, and tool enabled AI systems. The trainer will teach learners how to build AI solutions that can interact with tools, APIs, data sources, and workflows while maintaining scope control, memory handling, and reliability. The role requires strong practical experience with conversational AI, agent frameworks, and real world deployment patterns. This position plays a key role in building applied AI capability across technical and non-technical users by combining conceptual clarity, structured frameworks, and hands on project execution.

Key Responsibilities Curriculum and Training Design • Design a complete training roadmap covering AI chatbots, personal AI assistants, and scope based AI agents • Structure learning paths from beginner to advanced levels • Create hands on projects, demos, and real world use cases • Adapt curriculum for both technical and non-technical audiences

Training Delivery • Conduct live training sessions, workshops, and guided build sessions • Demonstrate real time chatbot and AI agent creation • Teach prompt engineering, agent logic, and memory handling • Provide session recordings, documentation, templates, and examples

Beginner Level Training Coverage • Introduction to AI chatbots and AI agents • Differences between chatbots, assistants, and agents • LLM fundamentals and conversational AI basics • Prompting fundamentals for chatbots • Building no code or low code chatbots • Simple intent based and FAQ driven chatbots Intermediate Level Training Coverage

AI Chatbots • Context handling and conversation flow design • System prompts and role based behavior • Multi turn conversations • Tool and API calling basics • Knowledge base powered chatbots

Personal AI Assistants • Task automation such as email handling, scheduling, and reminders • Connecting assistants to documents, spreadsheets, and APIs • Personalization using user preferences and history • Guardrails and scope limitation techniques

Advanced Level Training Coverage

Scope Based AI Agents • Designing goal oriented AI agents • Defining agent scope, rules, and boundaries • Tool using agents with APIs, databases, and automations • Memory handling including short term, long term, and vector memory • Multi agent systems and agent coordination • Error handling, retries, and fallback logic

Production and Optimization • Performance optimization and cost control • Security, data privacy, and access control • Logging, monitoring, and evaluation • Deployment and scaling best practices

Tools and Platforms Instruction Chatbot and Agent Platforms • OpenAI and Azure OpenAI APIs • LangChain and LangGraph • LlamaIndex • RAG pipelines with vector databases • Bot frameworks for web chat, Telegram, and WhatsApp No Code and Low Code Tools • Botpress • Flowise • Voiceflow • Zapier and n8n for agent actions Vector Databases and Memory Systems • Pinecone • Weaviate • Chroma • FAISS Use Cases to Teach • Customer support chatbots • Internal knowledge assistants • Personal productivity AI tools • Sales and marketing agents • HR and onboarding assistants • Operations and workflow automation agents

Required Skills and Competencies Technical Skills • Strong understanding of large language models and conversational AI • Experience building AI chatbots and agents end to end • Knowledge of RAG systems, embeddings, and vector databases • API integration and automation experience • Ability to debug, refine, and improve AI behavior Teaching and Communication Skills • Proven experience as a trainer, mentor, or instructor • Ability to simplify complex AI concepts • Strong communication and presentation skills • Practical and project focused teaching approach

Preferred Qualifications • Experience training enterprise or startup teams • Background in automation, backend development, or data engineering • Experience designing multi agent systems • Portfolio of deployed AI chatbots or AI agents

Deliverables and Expectations • End to end training curriculum from beginner to advanced • Hands on chatbot and AI agent projects • Prompt templates, agent blueprints, and workflows • Sample production ready AI agents • Post training support and mentorship

Evaluation Criteria • Depth of AI chatbot and agent expertise • Practical applicability of training content • Quality and reliability of sample AI agents • Teaching clarity and learner engagement

How to Apply Interested candidates can apply here on LinkedIn. For faster processing and priority review, please also share your updated resume at

careers@dagchain.network

to help us track and review your application efficiently.