Ai Engineer

Cardinal Integrated Technologies Inc

  • Santa Clara, CA
  • 8 days ago

    Highlights

    Skill 2 Architect and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources, including document chunking, embedding generation, and retrieval systems. " Architect and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources, including document chunking, embedding generation, and retrieval systems.

    Numbers & Facts

    LocationSanta Clara, CA

    Description

    Role: AI Engineer(23537-1)
    Duration: 6-12+ Months Contract
    Location: Santa Clara, CA (5 Days Onsite)

    Must Have Skills

    Skill 1 Deep proficiency in AI-centric libraries such as TensorFlow, PyTorch, and Hugging Face Transformers.
    Skill 2 Architect and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources, including document chunking, embedding generation, and retrieval systems.
    Skill 3 Design, develop, and deploy Custom AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models.

    Good To have Skills
    Skill 1 Design MS Copilot Studio Agent Builder advanced skills, including custom plugin development.

    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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