Experience: 10+ Years in IT Industry

Teaching Experience: Minimum 3+ Years

Role: Freelancing GenAI Trainer

About the Role

We are looking for an experienced Senior AI/GenAI Industry Trainer with strong industry expertise, hands-on technical experience, and a passion for teaching emerging technologies.

The ideal candidate will possess a strong background in Artificial Intelligence, Machine Learning, Generative AI, Large Language Models (LLMs), AI Agents, Cloud Technologies, and Software Architecture.

This role requires a technology professional who can bridge the gap between theoretical knowledge and real-world industry implementation. The candidate will be responsible for delivering practical, engaging, and industry-focused training programs for working professionals, managers, technology leaders, and business leaders.

The ideal candidate should have experience building and deploying AI-powered applications, implementing enterprise AI solutions, and delivering high-quality technical training.

Key Responsibilities

Training & Knowledge Delivery

- Deliver high-quality live training sessions on Artificial Intelligence, Machine Learning, Generative AI, LLMs, AI Agents, Cloud Technologies, and related emerging technologies.
- Conduct interactive, discussion-based, and practical learning sessions for working professionals, managers, and business leaders.
- Explain complex technical concepts in a easy, structured, and engaging manner.
- Design and deliver training programs aligned with skilled and enterprise learning requirements.
- Encourage learner participation through discussions, practical exercises, demonstrations, and real-world case studies.
- Mentor learners on industry practices, technical implementation, and emerging technology trends.

Technical Content Development

- Design and develop structured training content, presentations, hands-on labs, assignments, demonstrations, and project-based learning activities.
- Create practical exercises covering GenAI application development, RAG pipelines, AI Agents, and enterprise AI use cases.
- Continuously update training content based on evolving AI technologies, industry practices, and enterprise requirements.
- Ensure training programs provide practical knowledge that learners can apply in real-world projects.

Industry & Enterprise Application

- Share real-world industry experiences, enterprise implementations, technical challenges, failures, and lessons learned.
- Demonstrate how AI, GenAI, and LLM-based solutions are designed, developed, integrated, and deployed in enterprise environments.
- Connect theoretical concepts with practical implementation and business use cases.




- Help learners understand enterprise AI adoption, solution architecture, scalability, security, and performance considerations.
- Support learners in understanding customer requirements, solution design, and technical delivery.

Required Technical Skills & Expertise

Artificial Intelligence & Generative AI

- Strong practical experience in Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI.
- Hands-on experience with Python programming and AI/ML frameworks.
- Strong understanding of Large Language Models (LLMs), prompt engineering, context engineering, and LLM APIs.
- Experience building and deploying real-world GenAI applications.
- Knowledge of cloud-based AI/ML platforms and enterprise technology ecosystems.

LLM Engineering & RAG

- Hands-on experience developing Retrieval-Augmented Generation (RAG) pipelines using LangChain, LlamaIndex, or similar frameworks.
- Practical experience with vector databases, embeddings, semantic search, document ingestion, chunking, and retrieval strategies.
- Experience building multimodal and document intelligence applications.
- Understanding of hallucination mitigation, context management, and retrieval optimization.

AI Agents & Agentic Workflows

- Practical experience building AI Agents and agentic workflows.
- Strong understanding of tool calling, function calling, agent orchestration, and multi-agent systems.
- Hands-on experience with Model Context Protocol (MCP) and agent integration patterns.
- Understanding of planning, memory, state management, and human-in-the-loop (HITL) systems.
- Familiarity with agentic frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or similar technologies.

AI Evaluation, Security & LLMOps

- Working knowledge of AI evaluation, testing, benchmarking, observability, debugging, and performance optimization.
- Experience implementing AI security practices, including prompt injection protection, access control, and audit logging.
- Understanding of responsible AI, governance, and guardrails for production AI applications.
- Practical knowledge of LLMOps, containerization using Docker, and cloud deployment of AI applications.
- Familiarity with monitoring, reliability, scalability, and production readiness of AI systems.

Model Selection & Optimization





- Familiarity with Small Language Models (SLMs), fine-tuning, and model optimization techniques.
- Ability to explain model-selection trade-offs between hosted LLMs, SLMs, and fine-tuned models.
- Understanding of cost, latency, performance, scalability, and infrastructure considerations in AI solution design.

Software Architecture & Cloud Technologies

- Solid understanding of software architecture, enterprise technology, APIs, integrations, and cloud infrastructure.
- Experience with real-world projects involving architecture design, enterprise implementations, deployments, or AI transformation initiatives.
- Ability to explain scalable, secure, and production-ready AI application architecture.

Mandatory Qualifications & Experience

- 10+ years of experience in the IT industry is mandatory.
- Minimum 3+ years of teaching, technical training, mentoring, or instructional delivery experience.
- Strong practical experience in AI, Machine Learning, Generative AI, LLMs, Cloud Technologies, and Software Architecture.
- Demonstrated experience working on real-world enterprise technology projects and AI implementations.
- Experience delivering technical training to working professionals, technology teams, managers, or business leaders.
- Strong communication, presentation, mentoring, and facilitation skills.
- Ability to simplify complex technical concepts for diverse audiences.
- Comfortable conducting interactive, discussion-based, and hands-on learning sessions.

Customer-Facing & Solution Delivery Experience

- Exposure to customer-facing technical engagements, including customer discovery and requirements gathering.
- Ability to understand business challenges and translate them into technical solutions.
- Experience with solution architecture, technical consulting, system integration, and implementation.
- Ability to communicate technical solutions effectively to both technical and non-technical stakeholders.
- Experience supporting enterprise AI adoption, technical delivery, or AI transformation initiatives.

Ideal Candidate Profile The ideal candidate is an experienced technology professional who combines deep industry knowledge with strong training and mentoring capabilities.

The candidate should be able to demonstrate how AI and GenAI technologies are actually used in the industry, rather than focusing only on theoretical concepts.

- We are looking for someone who can bring real-world projects, practical implementation experience, enterprise use cases, and industry insights into the learning environment, helping professionals develop the skills required to succeed in the evolving AI ecosystem.

📌 Freelancing Gen AI Trainer (India)
🏢 INTTRVU.ai
📍 India