Highlights

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 2 - Design, develop, and deploy Custom AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models.

Numbers & Facts

LocationSanta Clara, CA

Description

Role: Gen AI Project Manager(23527-1)

Duration: 6-12+ Months Contract

Location: Santa Clara, CA (5 Days onsite)

Must Have Skills

Skill 1 - Demonstrate advanced programming expertise, particularly in Python, with deep proficiency in AI-centric libraries such as TensorFlow, PyTorch, and Hugging Face Transformers

Skill 2 - Design, develop, and deploy Custom AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models

Skill 3 - Ensure robust data handling practices including cleaning, labeling, and structuring datasets for generative AI workflows

Good To have Skills -

Skill 1 - prompt engineering, and secure data handling

Mandatory if Applicable

Domain Experience (If any) - Gen AI Project Manager

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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