Remote Product Cloud AI Engineer (GCP + AWS)

Augusta Hitech; United States; Hybrid; USD 83,000 - 165,000; Part time

Job summary

Augusta Hitech is seeking a Product Cloud Engineer for a contract, part-time, remote role based in the United States. You will design and implement scalable cloud architectures across Google Cloud Platform and Amazon Web Services, and integrate AI capabilities into our product ecosystem.

This ad-hoc, hourly position requires hands-on experience with cloud-native AI services and model deployment, with US-based authorization.

Qualifications

• Deep, hands-on experience building product architectures on multiple cloud platforms.

Responsibilities

• Cloud Architecture: Design, build, and optimize product-focused cloud infrastructure across GCP and AWS environments.
• AI Integration: Leverage AI/ML services to integrate intelligent features into product architectures.
• Ad-Hoc Engineering: Provide expert guidance and architectural execution on a flexible, as-needed project basis.

Skills

GCP

AWS

AI/ML

Cloud Architecture

Product Cloud Engineer

Job description

Employment Type: Contract / Part-Time (As-Needed)

Location: Remote (US-Based)

Job Overview

We are seeking an experienced Product Cloud Engineer with deep expertise in both Google Cloud Platform (GCP) and Amazon Web Services (AWS) to assist on an as-needed basis. In this role, you will design and build robust, scalable cloud architectures for our product offerings and integrate AI capabilities into our ecosystem.

Key Responsibilities

Cloud Architecture: Design, build, and optimize product-focused cloud infrastructure across both GCP and AWS environments.

AI Integration: Leverage AI/ML services and frameworks to integrate intelligent features into product architectures.

Ad-Hoc Engineering: Provide expert guidance, troubleshooting, and architectural execution on a flexible, as-needed project basis.

Requirements & Qualifications

Location: Must be located in the United States (US Citizen or Permanent Resident).

Cloud Expertise: Deep, hands-on experience building product architectures on both GCP and AWS.

AI Experience: Direct experience deploying AI/ML models, tools, or native cloud AI services.

Flexibility: Comfortable working on an hourly, ad-hoc basis depending on project demand and workload.

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