Nityo Infotech

GENAI Engineer

Nityo InfotechContract
California
8 - 10 YearsFeb 25th, 2026
68 ViewsBe an Early Applicant
Required Skillset:
PythonPower AutomateHugging Face TransformersGenerative AITensorFlowPyTorchLLMsSynthetic data generationRetrieval-Augmented Generation (RAG)Multi-modal modelsData pre-processingData augmentationData cleaningData labelingData structuringMS Copilot Studio Agent BuilderCustom plugin developmentAdaptive orchestrationContextual memory managementDynamic prompt engineeringSecure data handlingMulti-turn agentsTrigger managementMessage triggersData triggersScheduled triggersWebhook triggers

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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