GEN AI Architect with Google Cloud Platform

  • Louisville, KY
  • Posted 11 hours ago | Updated 11 hours ago

Overview

On Site
Hybrid
$50 - $90
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 36 Month(s)
Able to Provide Sponsorship

Skills

Artificial Intelligence
Cloud Computing
Cloud Storage
Collaboration
Continuous Delivery
Continuous Integration
Data Flow
Docker
Engineering Design
Generative Artificial Intelligence (AI)
Good Clinical Practice
Google Cloud
Google Cloud Platform
Java
Kubernetes
LangChain
Large Language Models (LLMs)
Lifecycle Management
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Management
Mentorship
Microsoft Azure
Optimization
Orchestration
Privacy
Programming Languages
Prompt Engineering
PyTorch
Python
Roadmaps
Scalability
Semantics
TensorFlow
Training
Use Cases
Vector Databases
Vertex

Job Details

GEN AI Architect with Google Cloud Platform

Location: Louisville, KY

Duration: 12+ Months (Contract)

We are seeking an experienced and innovative Generative AI Architect to lead the design, development, and deployment of cutting-edge AI/ML solutions leveraging the Google Cloud Platform (Google Cloud Platform). The ideal candidate will have deep expertise in Large Language Models (LLMs), RAG systems, and production-grade MLOps using Vertex AI.

Key Responsibilities

  • AI/ML Architecture: Architect and implement end-to-end AI/ML and Generative AI solutions on Google Cloud Platform using core services like Vertex AI, BigQuery, Cloud Storage, Cloud Composer, and Dataflow.

  • LLM Development: Develop, fine-tune, and integrate Large Language Models (LLMs) into critical enterprise applications, focusing on robust and scalable performance.

  • GenAI Pipeline Engineering: Design and build advanced Generative AI pipelines, including complex Retrieval-Augmented Generation (RAG) systems, utilizing frameworks such as LangChain and Semantic Kernel, and integrating with Vector Databases.

  • Collaboration & Strategy: Partner with cross-functional business and technical teams to identify, prioritize, and translate high-impact GenAI use cases into technical roadmaps and deliverable solutions.

  • Responsible AI: Ensure all deployed AI systems adhere to strict Responsible AI principles, data privacy regulations, and enterprise security standards.

  • Optimization & Scaling: Optimize model performance, scalability, and cost efficiency in production environments on Google Cloud Platform.

  • Mentorship: Provide technical guidance and mentorship to junior engineers, contributing to the establishment of best practices in AI engineering and MLOps.

Required Skills and Experience

< data-path-to-node="7">Google Cloud Platform & Cloud Expertise</>

  • Strong proficiency in the core Google Cloud Platform (Google Cloud Platform) AI/ML and data services: Vertex AI (training, deployment, monitoring), BigQuery, Cloud Spanner, Cloud Functions, and Pub/Sub.

  • Hands-on experience with pipeline orchestration tools like Cloud Composer or Cloud Dataflow.

< data-path-to-node="9">Generative AI & LLMs</>

  • Expertise in working with and deploying Large Language Models (LLMs), including Google's Gemini family or similar models.

  • Proven hands-on experience with Prompt Engineering techniques (e.g., Zero-shot, Few-shot, Chain-of-Thought).

  • Deep knowledge of frameworks like LangChain and experience utilizing external APIs like Azure/OpenAI APIs.

  • Demonstrable experience integrating and managing data in Vector Databases for RAG implementations.

< data-path-to-node="11">Engineering & MLOps</>

  • Expertise in programming languages like Python and/or Java.

  • Strong background in leading AI/ML frameworks (TensorFlow, PyTorch).

  • Familiarity with containerization and orchestration using Docker and Kubernetes.

  • Understanding of CI/CD pipelines for model deployment and lifecycle management.

  • Solid comprehension of Responsible AI, data privacy, and model governance best practices.

Key Words to Search in Resume

To ensure your application is recognized, please highlight experience with the following:

Large Language Models (LLMs), Gemini, Vertex AI, Big Query, Cloud Storage, Cloud Composer, Dataflow, AI, ML, RAG, LangChain, Vector Databases.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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