AI/ML Architect with GCP

NAM Info Inc; Louisville (KY); Remote; USD 138,000 - 207,000; Full time

Job summary

NAM Info Inc. in Louisville, KY seeks a Senior GCP AI/ML Architect to lead cloud AI architecture, data engineering, GenAI/RAG, agentic AI, and MLOps initiatives. You will design enterprise-grade AI platforms, implement scalable data pipelines, and drive cost-efficient, secure AI solutions.

Responsibilities include building AI/ML models with GCP tools, migrating data pipelines, and implementing CI/CD with Vertex AI Pipelines. Remote-friendly, with a focus on scalable, enterprise-grade deployments.

Qualifications

• Design enterprise-grade AI/ML platforms and cloud infrastructure.
• Architect data pipelines and MLOps workflows for GenAI/RAG and agentic AI.
• Develop AI/ML models using GCP services, Vertex AI, and Gemini.

Responsibilities

• Design and implement enterprise-grade AI platforms, including RAG and agentic AI solutions.
• Develop AI/ML models using GCP 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 GKE, Cloud Run, and BigQuery.
• Architect migration pipelines from on-premises to Azure Data Lake Storage.
• Design and maintain Azure Data Factory pipelines for multi-source ingestion.
• Transform 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 stakeholders.
• Manage high-volume unstructured data with optimized performance and cost.
• Establish data quality checks, logging, traceability, and audit controls.
• Establish AI safety guardrails and monitor model performance and costs.
• Collaborate with cross-functional teams using Agile methodologies.

Skills

GCP

Vertex AI

Gemini

Azure Data Factory

ADLS

Azure Databricks

Terraform

TensorFlow

PyTorch

Python

SQL

APIs

Tools

TensorFlow

PyTorch

Python

Job description

Role: Senior GCP AI/ML Architect Data Engineering & Generative AI

Location: Louisville, KY (Remote).

Duration: 6+ Months

Job Summary

• Primary Skills: GCP, 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 GCP 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.