AI Engineer

Responsibilities:

• Demonstrate advanced programming expertise, particularly in Python, with deep proficiency in AI-centric libraries such as TensorFlow, PyTorch, and Hugging Face Transformers.
• Architect and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources, including document chunking, embedding generation, and retrieval systems.
• Design, develop, and deploy Custom AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models.
• Implement and manipulate complex algorithms essential for developing and optimizing generative AI models.
• Manage data pipelines involving data pre-processing, augmentation, and synthetic data generation to enhance model training and performance.
• Ensure robust data handling practices including cleaning, labeling, and structuring datasets for generative AI workflows.
• Design MS Copilot Studio Agent Builder advanced skills, including custom plugin development, adaptive orchestration of multiple AI skills and APIs, contextual memory management, dynamic prompt engineering, and secure data handling.
• Agent Orchestration: Build multi-turn agents that adapt and chain AI skills and APIs.
• Trigger Management: Configure message, data, scheduled, and webhook triggers.
• Automation Workflow: Design workflows with Power Automate for task automation.
• Flow Design: Create logical, scalable flows for complex business processes.
• Tool Integration: Use Copilot s built-in connectors to integrate enterprise apps and services seamlessly.