Generative AI & AI Engineering Tutor / Trainer

Generative AI & AI Engineering Tutor / Trainer

Location: Hyderabad, Telangana On-site

Overall Experience: 5–10 Years

Gen AI Experience: Preferably 2–3+ years of strong hands-on Generative AI / LLM experience

Engagement: Long-term teaching engagement — 2–3 years

Schedule: Monday–Saturday, 9:00 AM–2:00 PM

Batch Size: 80–100 students

Batch Duration: 3 months

About the Program

We are running a practical Data Engineering Skill Development Program designed to prepare graduates for careers in

modern Data Engineering. The program combines Python + SQL + Data Engineering + Generative AI. Each batch runs for

three months and typically consists of 80–100 students. The program includes classroom sessions, hands-on labs,

assignments, assessments, mentoring and an integrated capstone. We are looking for a Generative AI & AI Engineering

Tutor who can teach students how to understand and practically apply Generative AI to software development, SQL and Data

Engineering.

Key Responsibilities

• Conduct Gen AI classroom sessions Monday–Saturday, 9:00 AM–2:00 PM at our Hyderabad training institute.
• Teach Generative AI concepts from fundamentals through practical application.
• Conduct hands-on Gen AI labs for batches of 80–100 students.
• Teach students how to use Gen AI for Python, SQL and Data Engineering.
• Develop and evaluate practical assignments, exercises and assessments.
• Conduct doubt-clearing and problem-solving sessions.
• Evaluate student assignments and projects.
• Mentor students during the Gen AI component of the final capstone.
• Teach students to validate AI-generated code and SQL rather than blindly trusting AI output.
• Introduce students to RAG and practical LLM application development.
• Teach responsible and secure use of Generative AI.
• Coordinate with Python, SQL and Data Engineering tutors.

Curriculum

1. Gen AI Foundations

• AI vs ML vs Deep Learning vs Generative AI
• Large Language Models
• Tokens and context windows
• Embeddings
• Inference
• Capabilities and limitations
• Hallucinations

2. Prompt Engineering

• Effective prompting
• Context and constraints
• Few-shot examples
• Structured outputs
• Iterative prompting
• Prompt evaluation

3. Gen AI for Python

• Code generation
• Code explanation
• Debugging
• Refactoring
• Documentation
• Unit-test generation
• Code review
• AI-assisted ETL development

4. Gen AI for SQL

• Natural language to SQL
• SQL explanation
• SQL debugging
• SQL optimization
• Dialect conversion
• Test-case generation
• Validating AI-generated SQL

5. Gen AI for Data Engineering

• Pipeline design assistance
• ETL/ELT design
• Data-quality rule generation
• PySpark assistance
• Airflow DAG generation
• Pipeline documentation
• Architecture analysis
• Troubleshooting

6. RAG

• RAG architecture
• Chunking
• Embeddings
• Vector databases
• Retrieval
• Context injection
• Generation
• Evaluation

7. Responsible Gen AI

• Hallucinations
• Incorrect code/SQL
• PII and sensitive information
• Prompt injection
• Security and privacy
• Human validation

8. Gen AI Capstone

• Build a Data Engineering Assistant
• Data dictionary/document set
• SQL generation and explanation
• Pipeline documentation
• RAG-based retrieval
• Evaluation and limitations

Candidate Profile — Must Have

• 5–10 years of overall technology/engineering experience.
• Strong hands-on experience with Generative AI / LLM applications.
• Preferably 2–3+ years of practical Gen AI experience.
• Strong Python knowledge and good SQL understanding.
• Understanding of Data Engineering concepts.
• Practical experience using Gen AI for software or data engineering.
• Strong communication and classroom presentation skills.
• Ability to simplify complex technical concepts for graduates.
• Ability to conduct practical sessions for large batches of 80–100 students.
• Passion for teaching, mentoring and developing students.
• Willingness to work on-site in Hyderabad.
• Ability to teach Monday–Saturday, 9:00 AM–2:00 PM.
• Willingness to commit to a 2–3 year engagement.

Preferred

• OpenAI / ChatGPT, Claude, Gemini or similar LLM platforms.
• GitHub Copilot or AI coding assistants.
• LangChain or LlamaIndex.
• RAG, vector databases and embeddings.
• AI agents.
• Python LLM/AI libraries.
• AWS AI/ML services and Data Engineering platforms.
• Prior corporate training, classroom teaching, bootcamp or student mentoring experience.