Generative AI Training Engineer Internship

About Examate

Examate is an industry-oriented technical training and placement preparation organization. We collaborate with engineering colleges to deliver structured training programs covering programming, emerging technologies, technical assessments, interview preparation, and placement readiness.

Job Overview

We are seeking enthusiastic, technically proficient, and passionate individuals as Generative AI Training Engineer Interns. Selected candidates will deliver technical training, mentor students, conduct practical demonstrations, and help students develop industry-relevant technical competencies. A good understanding of Python Programming, Generative AI, Large Language Models (LLMs), Prompt Engineering, and AI applications is required, along with excellent communication skills and a passion for teaching and mentoring. This opportunity is for final-year B.Tech/B.E. students and engineering graduates interested in technical training, mentoring, and Generative AI. This is a 3-month paid internship with an opportunity for full-time employment based on performance.

Key Responsibilities

• Deliver approximately 6 hours of technical training sessions per day.
• Teach Python, Generative AI, Large Language Models (LLMs), Prompt Engineering, and related AI technologies based on the assigned curriculum.
• Explain technical concepts clearly through interactive sessions, practical examples, and live demonstrations.
• Conduct hands-on coding sessions and guide students in developing AI-powered applications and mini-projects.
• Introduce practical concepts such as RAG, vector databases, and Agentic AI.
• Conduct assessments, clarify technical doubts, and monitor student learning progress.
• Prepare training materials, assignments, presentations, and practical coding exercises.
• Coordinate with Examate's training team, complete assigned syllabi on time, and maintain professional classroom standards.

Requirements & Tech Stack

Required Technical Skills

• Python Programming: Strong understanding of Python fundamentals, OOP, programming logic, and problem-solving.
• AI & Machine Learning: Basic knowledge of Artificial Intelligence, Machine Learning, Deep Learning, and Natural Language Processing (NLP).
• Generative AI & LLMs: Understanding of Generative AI, Large Language Models, Transformer fundamentals, tokens, and embeddings.
• Prompt Engineering: Knowledge of prompting techniques, prompt optimization, and effective LLM interactions.
• LLM APIs: Basic understanding of API integration and building AI-powered applications.
• Problem-Solving: Good programming, debugging, analytical, and logical thinking skills.

Preferred / Additional Technical Skills

Knowledge or practical exposure to the following will be an added advantage:

• Retrieval-Augmented Generation (RAG) and vector databases.
• LangChain, LlamaIndex, or similar GenAI frameworks.
• Agentic AI, AI agents, and tool-calling workflows.
• Hugging Face and open-source AI models.
• Streamlit, Gradio, FastAPI, Git, and GitHub.
• Hands-on AI projects such as chatbots, AI assistants, or document-based question-answering systems.

Note: Advanced knowledge of every technology is not mandatory. Candidates with strong fundamentals, practical understanding, and the ability to learn and teach effectively are encouraged to apply.

Qualifications

• Final-year B.Tech/B.E. students and engineering graduates.
• Candidates from CSE, IT, AI & ML, Data Science, and related technical backgrounds are preferred.
• Freshers with strong technical knowledge and good communication skills are encouraged to apply.
• Good understanding of Python Programming and Generative AI fundamentals.
• Strong analytical thinking, logical reasoning, and problem-solving abilities.
• Excellent communication, presentation, and interpersonal skills.
• Genuine interest and enthusiasm for teaching, training, and mentoring engineering students.
• Ability to simplify technical concepts and explain them effectively to beginners.
• Willingness to work six days per week and handle assigned technical training sessions.
• Willingness to travel or relocate to assigned training locations based on company requirements.
• Previous teaching or mentoring experience is an added advantage but is not mandatory.

Internship Details

• Company: Examate
• Position: Generative AI Training Engineer Intern
• Opportunity Type: Paid Internship with Full-Time Employment Opportunity
• Internship Duration: 3 Months
• Monthly Stipend: ₹20,000–₹30,000 (based on performance and evaluation)
• Working Days: 6 Days per Week
• Daily Engagement: Approximately 6 Teaching Hours
• Work Mode: On-site
• Work Location: Assigned Training Locations / Partner Engineering Colleges
• Eligible Candidates: Final-year B.Tech/B.E. students and engineering graduates
• Employment Opportunity: Full-time employment consideration based on performance following successful internship completion.

Benefits & Perks

• Paid Internship: Monthly stipend of ₹20,000–₹30,000, based on performance and company policies.
• Accommodation Facilities: Accommodation support will be provided as per company arrangements.
• Food Facilities: Food support during the internship, as applicable.
• Travel Support: Travel assistance for assigned training locations according to company policy.
• Practical Industry Exposure: Gain hands-on experience in Generative AI, LLMs, Prompt Engineering, and AI application development.
• Professional Teaching Experience: Opportunity to train and mentor engineering students in industry-relevant technologies.
• Technical Skill Development: Strengthen technical expertise through practical implementation, training preparation, and continuous learning.
• Communication & Leadership Development: Improve presentation skills, classroom management, communication, and professional confidence.
• Career Development: Gain experience in technical training, mentoring, and emerging AI technologies.
• Full-Time Employment Opportunity: High-performing interns may be considered for full-time roles at Examate based on performance and organizational requirements.

Recruitment & Selection Process

The recruitment process consists of two screening rounds designed to evaluate candidates' technical knowledge, communication skills, and suitability for technical training and mentoring responsibilities.

Round 1 – Technical Interview

Candidates will undergo a technical interview to evaluate their understanding of Generative AI and related technologies.

Evaluation Areas:

• Python Programming fundamentals.
• Artificial Intelligence and Machine Learning concepts.
• Generative AI and Large Language Models (LLMs).
• Prompt Engineering and LLM APIs.
• RAG and Agentic AI fundamentals, where applicable.
• Technical problem-solving and practical understanding.
• Ability to explain technical concepts clearly and effectively.

Candidates who successfully clear the technical interview will proceed directly to the Final HR Interview.

Round 2 – Final HR Interview

Shortlisted candidates will attend the final HR interview to evaluate:

• Communication and interpersonal skills.
• Passion for teaching, training, and mentoring students.
• Professional attitude, confidence, and behavioral competencies.
• Willingness to travel or relocate based on company requirements.
• Availability and commitment toward internship responsibilities.
• Career aspirations and interest in technical training.
• Overall suitability for the role and alignment with Examate's professional expectations.

Final Selection & Onboarding

Candidates who successfully clear both interview rounds will be considered for the 3-month paid Generative AI Training Engineer Internship at Examate. Selected candidates will receive further communication regarding the offer, internship terms, assigned training locations, and onboarding procedures.

Internship-to-Full-Time Employment Opportunity

This is an Internship-to-Full-Time Employment Opportunity. Selected candidates will initially undergo a 3-month paid internship, during which their technical expertise, teaching effectiveness, communication skills, professionalism, and overall performance will be evaluated. Upon successful completion of the internship, candidates may be considered for full-time employment at Examate. Full-time employment consideration will be based on:

• Technical performance and subject expertise.
• Teaching effectiveness and student engagement.
• Communication and presentation abilities.
• Professional conduct and punctuality.
• Ability to manage assigned responsibilities independently.
• Overall internship performance and organizational requirements.

Full-time employment is subject to performance evaluation, organizational requirements, and management approval. Conversion to full-time employment is not automatically guaranteed.

Why Join Examate?

• Gain professional experience in Generative AI and technical mentoring.
• Work directly with engineering students and contribute to their technical development.
• Strengthen technical knowledge through practical teaching and hands-on implementation.
• Develop professional communication, presentation, and leadership abilities.
• Gain exposure to industry-oriented training programs and placement preparation activities.
• Work with modern AI technologies, tools, and practical applications.
• Receive applicable food, accommodation, and travel support.
• Build a career in technical training, AI education, and emerging technologies.
• Get an opportunity to transition into full-time employment based on performance.

Who Should Apply?

We are looking for individuals who are not only technically proficient but also genuinely passionate about teaching, training, and mentoring engineering students. If you possess strong Python and Generative AI fundamentals, enjoy explaining technical concepts, have effective communication skills, and want to contribute to the professional development of future engineers, we encourage you to apply. Join Examate and become part of our mission to develop the next generation of technically skilled, confident, and industry-ready professionals.