GENAI Engineer
Job Description
About the Role:
We are seeking a highly skilled and innovative AI Engineer to join our team and lead the development of intelligent AI agents and Retrieval-Augmented Generation (RAG)-based applications. This role is ideal for someone passionate about pushing the boundaries of applied AI, with hands-on experience in building scalable, production-grade Generative AI (GenAI) systems and advanced Copilot Studio agent capabilities.
Key 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.
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