Non-Technical AI Trainer / Applied AI TrainerLocation: Hyderabad / Secunderabad

Employment Type: Full-Time / Contractual

Work Mode: Primarily On-site

Experience: 3–6 years

Qualification: Bachelor's degree or equivalent; MBA / business-related qualification is an advantage

About the RoleWe are looking for a Non-Technical AI Trainer / Applied AI Trainer who can help working professionals and learners understand how to use Generative AI effectively in real-world professional environments.

This is not a coding, AI/ML engineering, or data science role.

The ideal candidate will be a strong AI practitioner who understands how Generative AI can be applied across business functions such as Marketing, Sales, Human Resources, Finance, Operations, Administration and other professional workflows.

The role combines AI expertise, business understanding, training/facilitation and professional judgment. The trainer should be able to move beyond simply demonstrating AI tools and teach learners how to use AI responsibly, critically evaluate outputs, improve their workflows and apply AI to practical workplace situations.

Key Responsibilities1.

Deliver Practical

Generative AI Training

- Conduct instructor-led training sessions on Generative AI and its practical applications.
- Explain AI concepts, capabilities, limitations and appropriate use cases in a simple, non-technical manner.
- Demonstrate practical applications of leading AI tools such as ChatGPT, Claude, Gemini, Microsoft Copilot and other relevant platforms.
- Teach participants how to select the appropriate AI tool based on the task, context and desired outcome.
- Keep training practical, business-oriented and relevant to real workplace scenarios.

2. Prompting & AI Interaction

- Teach practical prompting methodologies and frameworks.
- Help learners structure effective instructions, provide context, establish constraints and improve AI responses.
- Demonstrate iterative prompting and refinement techniques.
- Teach learners how to move from basic AI queries to structured professional workflows.
- Develop practical exercises that require learners to apply AI rather than simply observe demonstrations.

3. AI Output Evaluation & Quality Control

- Teach learners how to critically evaluate AI-generated content.
- Establish practical methods for checking accuracy, relevance, completeness, consistency and potential bias.
- Demonstrate fact-checking and verification techniques.
- Help learners identify hallucinations, unsupported claims and unreliable AI outputs.
- Review learner assignments and provide constructive, actionable feedback.
- Evaluate whether learners have used AI appropriately rather than merely producing an acceptable final answer.

The ability to critically assess another person's professional work is an important part of this role. 4. Business & Functional AI Applications

- Facilitate practical sessions demonstrating how AI can be incorporated into everyday professional workflows.
- Help learners identify suitable AI use cases within functions such as:
- Marketing
- Sales
- Human Resources
- Finance
- Operations
- Administration
- Customer-facing functions




- Conduct workflow-mapping exercises to identify opportunities for AI-assisted work.
- Help learners distinguish between tasks that should be automated, AI-assisted or handled entirely by humans.
- Develop practical business cases and examples based on real workplace scenarios.

5. No-Code AI & Workflow Automation

- Introduce learners to practical no-code AI workflows and automation.
- Demonstrate tools such as Zapier, Make and comparable AI-enabled automation platforms.
- Demonstrate AI-assisted workflows involving multiple tools and applications.
- Help learners understand basic AI chaining and workflow automation without requiring programming knowledge.
- Demonstrate the practical use of custom GPTs, AI assistants, Gems or comparable no-code AI solutions.

Programming or software development expertise is not required for this position. 6. Assignments, Projects & Capstone Evaluation

- Design and conduct practical assignments and workplace-based exercises.
- Evaluate individual learner submissions using defined assessment rubrics.
- Provide specific feedback on quality, reasoning, application and professional relevance.
- Facilitate practical projects and capstone activities.
- Assess whether learners can independently apply AI to a professional problem rather than simply reproduce material taught in class.
- Identify gaps in learner understanding and provide corrective guidance.

7. Case Studies & Practical Content Development

- Contribute to the development of practical AI case studies and exercises.
- Develop examples covering both successful and unsuccessful applications of AI.
- Incorporate real-world AI failures, verification challenges and judgment-based scenarios into training.
- Help create exercises where learners must determine whether an AI-generated output can be trusted, modified, verified or rejected.
- Continuously improve training material based on learner performance and emerging AI practices.

8.

Stay Current

With the AI Landscape

- Continuously track developments in Generative AI and major AI platforms.
- Stay updated on new capabilities, features, models and practical business applications.
- Experiment with new AI tools and evaluate their usefulness for professional workflows.
- Regularly update demonstrations, exercises and examples to reflect changes in the AI ecosystem.

Required Skills & ExperienceEssential

- 3–6 years of overall professional experience.
- At least 1–2 years of practical experience using Generative AI in a professional/business environment.
- Strong hands-on experience with tools such as ChatGPT, Claude, Gemini, Microsoft Copilot or equivalent platforms.
- Strong understanding of prompting and AI-assisted workflows.
- Ability to evaluate AI-generated content critically and identify inaccuracies or weaknesses.




- Ability to explain AI concepts to non-technical audiences.
- Robust presentation and facilitation skills.
- Strong written and verbal communication skills.
- Practical understanding of at least 2–3 business functions, such as Marketing, Sales, HR, Finance or Operations.
- Familiarity with no-code automation platforms such as Zapier, Make or similar tools.
- Experience creating or using custom GPTs, AI assistants, Gems or comparable no-code AI solutions.
- Ability to independently research and learn new AI tools and features.

Preferred

- Prior experience as a corporate trainer, professional trainer, consultant, facilitator, coach or learning & development professional.
- Experience training working professionals.
- Experience designing assignments, assessments, rubrics or practical projects.
- Consulting or cross-functional business experience.
- MBA or a business/management-related qualification.
- Experience applying AI within a specific professional function such as HR, Marketing, Sales, Finance, Operations or Administration.
- Experience developing case studies, workshops or professional learning content.

What We Are Looking ForThe ideal candidate is not simply someone who knows how to use AI tools. We are looking for someone who can:

Understand AI → Apply AI → Explain AI → Evaluate AI → Teach others to apply AI professionally.

The candidate should be comfortable demonstrating their own practical AI workflows and explaining why a particular approach works, where it can fail and how the output should be verified.

Strong trainers who have limited practical AI experience, as well as technically strong AI professionals who have little training or business exposure, may not be the right fit.

Candidate ProfileYou may be a good fit if you come from backgrounds such as:

- Corporate AI Trainer
- Generative AI Trainer
- AI Adoption Consultant
- AI Business Consultant
- AI Productivity Consultant
- Digital Transformation Consultant
- L&D; / Corporate Trainer with strong GenAI experience
- Business Consultant with significant hands-on GenAI experience
- Marketing / HR / Sales / Operations professional who has developed strong applied AI expertise

This is a non-technical AI training role. Coding, Python, machine learning engineering or model development experience is not required. CompensationCompensation will be aligned with prevailing market standards and will be commensurate with relevant experience, practical AI expertise, training capability and overall suitability for the role.

Candidates with stronger applied AI, cross-functional business exposure and professional training experience may be considered at a higher level.

Selection ProcessShortlisted candidates may be required to:

- Demonstrate practical use of Generative AI.
- Conduct a short sample training session.
- Explain an AI workflow for a real business scenario.
- Evaluate an AI-generated output and identify potential issues.
- Complete a practical assessment designed to evaluate AI application, communication and judgment.

We are particularly interested in candidates who can demonstrate how they have personally used AI to improve real professional work.

📌 Non-Technical AI Trainer / Applied AI Trainer (Hyderabad)
🏢 Welkin Enterprises
📍 Hyderabad