Google Cloud Platform GEN AI Architect and Prompt Engineer- Onsite in Las Vegas, NV

Overview

On Site
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 12 Month(s)
No Travel Required
Unable to Provide Sponsorship

Skills

Extensive hands-on experience with Google Cloud Platform specifically Vertex AI- Dialogflow CX and other conversational AI services.
Python
Prompt Engineering: Proven experience in crafting effective prompts for Large Language Models (LLMs) and generative AI.

Job Details

GEN AI Architect and Prompt Engineer

•    Technical Proficiency:
o    Google Cloud Platform: Extensive, hands-on experience with Google Cloud Platform, specifically Vertex AI, Dialogflow CX, and other conversational AI services.
o    Programming: Proficiency in programming languages like Python is essential for building integrations, automating tasks, and analyzing data.
o    APIs & Data: Experience with REST APIs, webhooks, and data management systems.
•    Conversational Expertise:
o    Linguistics: A strong understanding of human language, syntax, and conversational nuances.
o    Prompt Engineering: Proven experience in crafting effective prompts for Large Language Models (LLMs) and generative AI.
o    Conversation Building: Experience in designing and building engaging and logical conversations.

Responsibilities:

AI Architecture & Development / Support
•    Design and Implement AI Solutions: Architect, design, and deploy end-to-end conversational AI agents and virtual assistants on the Google Cloud Platform platform.
•    Platform Expertise: Utilize a deep knowledge of Google Cloud Platform AI technologies, including Vertex AI, Dialogflow CX, Conversational AI (CCAI), Playbooks, Conversational Agents and related services.
•    Integrations: Build and manage integrations between conversational agents and various backend systems, APIs, and other Google Cloud services.
•    Lifecycle Management: Manage the full lifecycle of AI agents, from initial proof-of-concept to production deployment and ongoing maintenance. This includes monitoring performance, troubleshooting issues, and implementing MLOps best practices.
Prompt Engineering & Conversation Building
•    Prompt Design: Craft and refine prompts and instructions for generative AI models to ensure accurate, relevant, and helpful responses.
•    Conversation Design: Design natural and effective conversational flows for both voice and chat agents. This involves defining user journeys, intents, entities, and state handlers.
•    Agent Tuning: Tune and optimize NLU (Natural Language Understanding) models and AI agent performance through data analysis and iterative refinement.
•    Content & Ethics: Ensure that AI-generated content is high-quality, on-brand, and adheres to responsible AI principles, including safety and fairness.
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