Senior AI Trainer – Generative AI, Agentic AI & Cloud AI Engineering

Location: Remote / Hybrid

Experience: 8 Years

About the Role

We are seeking an experienced Senior AI Trainer to design and deliver hands-on training programs in Generative AI, Agentic AI, RAG, LLM Engineering, Cloud AI Platforms, and Production AI Systems.

The ideal candidate combines deep technical expertise with a passion for mentoring engineers and helping organizations build enterprise-scale AI capabilities.

Key Responsibilities

- Deliver instructor-led and hands-on training in modern AI engineering technologies.
- Develop real-world projects, labs, assessments, and capstone assignments.
- Mentor learners on building production-ready AI applications.
- Train teams on AI architecture, deployment, governance, and best practices.
- Design learning paths for AI Engineers, ML Engineers, Solution Architects, and Developers.
- Stay current with emerging AI frameworks, cloud services, and industry trends.

Required Technical Expertise

Generative AI & LLMs

- GPT, Claude, Gemini, Llama and other foundation models
- Prompt Engineering and Context Engineering
- Function Calling and Tool Integration
- AI Evaluation, Guardrails, and Responsible AI

RAG & Knowledge Retrieval

- Retrieval-Augmented Generation (RAG)
- Embeddings and Vector Search
- Semantic Search and Hybrid Search
- Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS, pgVector)

Agentic AI

- AI Agents and Multi-Agent Systems
- Agent Orchestration




- MCP (Model Context Protocol)
- Human-in-the-Loop Workflows
- Enterprise AI Automation

AI Frameworks

- LangChain
- LangGraph
- LlamaIndex
- CrewAI
- AutoGen
- Semantic Kernel
- OpenAI Agents SDK

Programming & Application Development

- Python
- FastAPI
- REST APIs
- Pydantic
- SQL
- Streamlit or React

Machine Learning & AI Fundamentals

- Machine Learning and Deep Learning
- NLP
- Transformers
- Fine-Tuning
- PyTorch
- TensorFlow
- Hugging Face
- Scikit-Learn

Cloud & AI Platform Engineering

- AWS Bedrock, SageMaker, Lambda, S3
- Azure OpenAI, Azure AI Foundry, Azure AI Search
- Google Vertex AI and Gemini

AI Operations & Deployment

- Docker
- Kubernetes
- Terraform
- CI/CD
- MLOps / LLMOps
- MLflow
- Monitoring & Observability

Preferred Qualifications

- Experience delivering corporate AI upskilling programs.
- Solid solution architecture and consulting background.
- Experience integrating AI with enterprise platforms such as SAP, ServiceNow, Jira, or CRM systems.
- Relevant AWS, Azure, Google Cloud, or AI certifications.

What Success Looks Like The successful candidate will enable learners to design, build, deploy, and govern enterprise-grade AI solutions including RAG systems, Agentic AI applications, AI copilots, and cloud-native AI platforms.

If you are passionate about transforming engineers into next-generation AI professionals and have hands-on experience across the modern AI stack, we'd love to hear from

📌 Senior AI Trainer – Generative AI, Agentic AI & Cloud AI Engineering (Hyderabad)
🏢 ProArch Technologies
📍 Hyderabad