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.
- Robust 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.

📌 Generative AI & AI Engineering Tutor / Trainer (Hyderabad)
🏢 Sai Easwaramma Prerana Trust
📍 Hyderabad