Generative AI Trainer cum AI Developer

Job Overview

We are seeking a talented and motivated professional to join our team. This position offers competitive pay and strong career growth opportunities.

Job Title
Generative AI Trainer cum AI Developer
Job Summary
We are seeking a highly motivated and innovative Generative AI Trainer cum AI Developer to design, develop, implement, and train stakeholders on cutting-edge Artificial Intelligence and Generative AI solutions. The ideal candidate will have a strong technical background in AI/ML, Large Language Models (LLMs), prompt engineering, and AI application development, along with the ability to deliver engaging training programmes for students, professionals, and corporate clients.
This role combines hands-on AI development with knowledge-sharing responsibilities to help organisations adopt and maximise the value of Generative AI technologies.
Key Responsibilities
AI Development
Design, develop, test, and deploy Generative AI applications and AI-powered solutions.
Build applications using Large Language Models (LLMs) such as GPT, Claude, Gemini, and open-source models.
Develop AI chatbots, virtual assistants, copilots, knowledge management systems, and automation solutions.
Implement prompt engineering, RAG (Retrieval Augmented Generation), vector databases, and fine-tuning techniques.
Integrate AI solutions with enterprise applications, APIs, cloud platforms, and databases.
Monitor model performance and optimise AI systems for accuracy, efficiency, and scalability.
Stay updated on emerging trends, frameworks, and best practices in AI and machine learning.
Training & Knowledge Transfer
Design and deliver Generative AI training programmes, workshops, boot camps, and certification courses.
Create training materials, learning modules, case studies, hands-on exercises, and assessments.
Train students, educators, corporate employees, and business leaders on AI concepts and practical applications.
Conduct sessions on Prompt Engineering, AI Automation, ChatGPT, Microsoft Copilot, AI Ethics, and AI Productivity Tools.
Mentor learners on real-world AI projects and best implementation practices.
Evaluate training effectiveness and continuously improve learning content.
Consulting & Innovation
Assess business requirements and identify AI-driven opportunities.
Guide clients on AI adoption strategies and implementation roadmaps.
Promote responsible AI practices, governance, and ethical AI usage.
Support pre-sales activities, solution demonstrations, and proof-of-concept development.
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field.
2-8 years of experience in AI, Machine Learning, Software Development, or related domains.
Hands-on experience with Python and AI/ML libraries such as TensorFlow, PyTorch, LangChain, LlamaIndex, or similar technologies.
Strong understanding of Generative AI, LLMs, Prompt Engineering, NLP, and AI solution architecture.
Experience developing applications using OpenAI APIs, Azure AI Services, Google AI, or equivalent platforms.
Excellent communication, presentation, and facilitation skills.
Ability to explain complex AI concepts to both technical and non-technical audiences.
Preferred Skills
Experience with Microsoft Azure AI, Microsoft Copilot Studio, Azure OpenAI Service, or other cloud AI platforms.
Knowledge of vector databases, embeddings, semantic search, and RAG architecture.
Experience in AI automation tools and workflow platforms.
Familiarity with MLOps, model deployment, and AI governance frameworks.
Corporate training, instructional design, or teaching experience.
Relevant AI, Cloud, or Data Science certifications.
Key Competencies
Analytical thinking and problem-solving
Innovation and continuous learning
Training and facilitation excellence
Stakeholder management
Project execution and delivery
Communication and presentation skills
Team collaboration
Employment Type
Full-Time / Contract (as applicable)
Experience Level
Mid-Level to Senior-Level
Location
On-site / Hybrid / Remote (as applicable)
Performance Indicators (KPIs)
Successful delivery of AI training programmes and learner satisfaction scores.
Number of AI solutions developed and deployed.
Adoption and utilisation of AI tools by users.
Improvement in business productivity through AI implementations.
Training completion and certification success rates.
Client and stakeholder feedback.