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AI/ML Architect with Google Cloud Platform

Nam Info IncLouisville, KY🇺🇸United StatesPosted Oct 23, 2026

Why this role stands out

Accelerate your career by architecting cutting-edge Generative AI and MLOps solutions within a high-impact hybrid role that offers the perfect balance of professional flexibility and technical innovation. You will thrive in this position if you are a forward-thinking engineer passionate about leveraging Google Cloud and Azure ecosystems to build enterprise-scale AI platforms. Apply today to lead transformative projects and elevate your expertise at the forefront of the AI revolution.

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationLouisville, KY, United States
Posted2 days ago
SQLMLOpsBigQueryDatabricksGoogle CloudPyTorchPythonTensorFlowTerraformGenerative AIAzureKubernetesAgileCI/CDAzure Data FactoryDelta LakeRAG

Job description

Role: Senior Google Cloud Platform AI/ML Architect Data Engineering & Generative AI

Location: Louisville, KY (Remote).

Duration: 6+ Months

Job Summary

  • Primary Skills: Google Cloud Platform, Vertex AI, Gemini, Azure Data Factory, ADLS, Azure Databricks, Terraform
  • Role Focus: Cloud AI architecture, data engineering, GenAI/RAG, agentic AI, and MLOps.
  • Design, architect, and implement enterprise-grade AI/ML platforms and cloud infrastructure.
  • Develop AI solutions using Google Cloud Platform, Vertex AI, and Gemini.
  • Architect large-scale data migration pipelines from on-premises systems to Azure Data Lake Storage (ADLS).
  • Build and manage Azure Data Factory (ADF) pipelines for data ingestion and transformation.
  • Implement scalable data pipelines, AI models, RAG applications, and agentic AI solutions.
  • Ensure data quality, security, governance, performance, and cost efficiency.

Roles & Responsibilities

  • Design and implement enterprise-grade AI platforms, including RAG and agentic AI solutions.
  • Develop AI/ML models using Google Cloud Platform services, Vertex AI, and Gemini.
  • Build and manage data pipelines, model lifecycle processes, and MLOps/LLMOps workflows.
  • Implement CI/CD pipelines using Cloud Build and Vertex AI Pipelines.
  • Deploy scalable AI applications using Google Kubernetes Engine (GKE), Cloud Run, and BigQuery.
  • Architect large-scale migration pipelines from on-premises environments to Azure Data Lake Storage.
  • Design, develop, and maintain Azure Data Factory pipelines for multi-source data ingestion.
  • Transform and process data using Azure Databricks and Delta Lake.
  • Implement infrastructure automation using Terraform.
  • Develop AI/ML solutions using TensorFlow or PyTorch, Python, SQL, APIs, and data modeling.
  • Analyze data and deliver insights to business stakeholders.
  • Manage high-volume unstructured data with optimized performance and cost.
  • Implement data quality checks, logging, traceability, and audit controls.
  • Establish AI safety guardrails and monitor model performance, reliability, and costs.
  • Collaborate with cross-functional teams using Agile development methodologies.

Thanks & Regards:

John H

Sr Recuiter

Nam Info Inc

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