AI Cloud Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Cloud Engineer, lasting 12 years, with a pay rate of "unknown." Locations include various U.S. cities. Key skills required are cloud service adapter expertise, IaC for AI pipelines, and knowledge of cross-cloud networking.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
560
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🗓️ - Date discovered
September 11, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
Unknown
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
San Francisco, CA
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🧠 - Skills detailed
#Infrastructure as Code (IaC) #AI (Artificial Intelligence) #Cloud #Azure #AWS (Amazon Web Services) #GCP (Google Cloud Platform) #Compliance
Role description
AI Cloud Engineer
Location: San Francisco, CA / Santa Clara, CA / Mountain View, CA / Southfield, MI / Princeton, NJ / St. Louis, MO / Austin, TX / Seattle, WA
Duration: 12 years
Responsibilities:
Design and implement agent cloud adapters integrating with AgentCore, AgentSpace, and Azure Arc.
Build IaC templates and enforce compliance for cloud-native AI workloads.
Enable the Cloud Agent to provision, monitor, and optimize AI infrastructure across providers.
Requirements:
Expertise in cloud service adapters for AI platforms (AWS Bedrock, Azure AI Foundry, GCP Vertex).
Hands-on with IaC for AI pipelines and GPU-enabled infrastructure.
Knowledge of cross-cloud networking, hybrid cloud setups, and cost optimization.
Preferred:
Azure Arc or hybrid cloud expertise.
Familiarity with FinOps practices for AI workloads.
AI Cloud Engineer
Location: San Francisco, CA / Santa Clara, CA / Mountain View, CA / Southfield, MI / Princeton, NJ / St. Louis, MO / Austin, TX / Seattle, WA
Duration: 12 years
Responsibilities:
Design and implement agent cloud adapters integrating with AgentCore, AgentSpace, and Azure Arc.
Build IaC templates and enforce compliance for cloud-native AI workloads.
Enable the Cloud Agent to provision, monitor, and optimize AI infrastructure across providers.
Requirements:
Expertise in cloud service adapters for AI platforms (AWS Bedrock, Azure AI Foundry, GCP Vertex).
Hands-on with IaC for AI pipelines and GPU-enabled infrastructure.
Knowledge of cross-cloud networking, hybrid cloud setups, and cost optimization.
Preferred:
Azure Arc or hybrid cloud expertise.
Familiarity with FinOps practices for AI workloads.
