Core Services: Azure OpenAI, AI Search (RAG patterns), Document Intelligence, and Bot Service. Languages: Proficiency in Python (most critical) Machine Learning: Understanding of supervised/unsupervised learning and deep learning frameworks (PyTorch/TensorFlow). DevOps/MLOps: Managing model versioning, CI/CD for AI, and infrastructure via Azure ML Studio.

1Prompt Engineering & RAG: Designing effective prompts for Large Language Models (LLMs) and building Retrieval-Augmented Generation (RAG) pipelines to ground AI outputs in specific company data.

2 Model Selection and Integration: Identifying the right pre-trained models (like GPT-4, Llama 3, or BERT) for a specific business problem and integrating them into existing software architecture using APIs.

3 Agentic System Development: Building autonomous or semi-autonomous "AI Agents" capable of multi-step reasoning and task execution.

4 MLOps & Maintenance: Implementing CI/CD pipelines for models, monitoring performance for "drift" or safety issues, and managing scaling and cost footprints

5 Responsible AI: Configuring safety filters, guardrails, and auditing logs to ensure AI systems are ethical, fair, and compliant with regulations

📌 Ai Engineer 4th Aug Tuesday Virtual Interview Kolkata
🏢 Tata Consultancy Services
📍 Kolkata