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Temporary Cloud Operations Engineer Jobs in Georgia

AI Devops Engineer

Atlanta, GA · On-site

$50.75 - $69.50/hr

... s Engineer Location: Atlanta, GA 5 Month Contract Only W2 3 days hybrid onsite in Atlanta Top ... This role will focus on cloud architecture, Infrastructure as Code (IaC), AI/ML operations ...

DevOps Engineer

Atlanta, GA · On-site

$50.75 - $69.50/hr

... s Engineer Location: Atlanta, GA Act as a "deployment engineer" and perform the customer deployment ... Understanding of Cloud APIs and Cloud technologies specifically Azure & AWS * Terraform ...

Application Operations Engineer (SaaS) using AWS Duration: 12 + Months Type (Hybrid): Remote - 2 ... Managing Complex Applications hosted on cloud * Support Application maintenance activities

DevOps Engineer II

Lagrange, GA · Remote

$48 - $66/hr

... s Engineer II Location: 99% Remote Position Type: Full-time About Us Mountville Inc. is a forward ... Cloud Infrastructure Management: Configure, deploy, and manage Azure cloud resources with an ...

... s Engineer to support a fast-paced software development and infrastructure team. The ideal ... Support the development and deployment of cloud infrastructure in AWS, particularly EKS. * Support ...

DevOps Engineer

Augusta, GA · On-site

$300K/yr

... s Engineer to support a fast-paced software development and infrastructure team. The ideal ... Support the development and deployment of cloud infrastructure in AWS, particularly EKS. * Support ...

DevOps Engineer

Augusta, GA · On-site

$300K/yr

... s Engineer to support a fast-paced software development and infrastructure team. The ideal ... Support the development and deployment of cloud infrastructure in AWS, particularly EKS. * Support ...

Lead Cloud Engineer

Atlanta, GA · On-site

$53.50 - $71.75/hr

Collaborate with DevOps, security, and development teams to support CI/CD pipelines and automation . Required Skills * Strong expertise in AWS cloud architecture (EC2, S3, RDS, VPC, IAM, Lambda, API ...

... s Engineer to join our team and play a key role in automating and optimizing our software delivery ... Architect and manage Azure cloud services including AKS, App Service, ACE, APIM, AFD, ADF, Power ...

DevOps Engineer IV 4P/763

Atlanta, GA · On-site

$50.75 - $69.50/hr

... s Engineer IV Location: Atlanta, GA Duration: 6 Months Client: Southern Company Services Job ... The ideal candidate will have expertise in Google Cloud Platform (GCP) (preferred), Azure ...

DevOps Engineer II

Lagrange, GA · On-site

$41 - $56/hr

... s Engineer II Location: 99% Remote Position Type: Full-time About Us Mountville Inc. is a forward ... Cloud Infrastructure Management: Configure, deploy, and manage Azure cloud resources with an ...

DevOps Engineer 4

Atlanta, GA · On-site

$50.75 - $69.50/hr

This role focuses on designing, deploying, and maintaining cloud-based infrastructure and CI/CD ... s Engineer or in a similar role supporting cloud-based web applications . * Strong expertise with ...

DevOps Engineer

Atlanta, GA · On-site

$50.75 - $69.50/hr

Azure Cloud Engineering * Design, build, and maintain Azure cloud infrastructure using best ... Participate in operational reviews and continuous improvement initiatives Collaboration ...

DevOps Engineer

Atlanta, GA

$50.75 - $69.50/hr

Azure Cloud Engineering * Design, build, and maintain Azure cloud infrastructure using best ... Participate in operational reviews and continuous improvement initiatives Collaboration ...

Showing results 41-60

Temporary Cloud Operations Engineer information

What is the difference between Temporary Cloud Operations Engineer vs Cloud Systems Administrator?

AspectTemporary Cloud Operations EngineerCloud Systems Administrator
CertificationsCloud certifications (AWS, Azure, GCP)Similar cloud certifications, often with additional system admin credentials
Work EnvironmentProject-based, temporary assignments in cloud environmentsOngoing management of cloud infrastructure within organizations
Employer & Industry UsageTech companies, cloud service providers, consulting firmsLarge enterprises, managed service providers, IT departments

Temporary Cloud Operations Engineers focus on short-term cloud deployment and troubleshooting, while Cloud Systems Administrators handle ongoing cloud infrastructure management. Both roles require cloud certifications and work in similar environments, but their scope and duration differ.

What are the most commonly searched types of Cloud Operations Engineer jobs in Georgia?

The most popular types of Cloud Operations Engineer jobs in Georgia are:

What are popular job titles related to Temporary Cloud Operations Engineer jobs in Georgia?

For Temporary Cloud Operations Engineer jobs in Georgia, the most frequently searched job titles are:

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The top searched job categories for Temporary Cloud Operations Engineer jobs in Georgia are:

What cities in Georgia are hiring for Temporary Cloud Operations Engineer jobs?

Cities in Georgia with the most Temporary Cloud Operations Engineer job openings:

$50.75 - $69.50/hr

Other

Posted 26 days ago


Job description

Title : AI Devops Engineer

Location: Atlanta, GA

5 Month Contract

Only W2 

3 days hybrid onsite in Atlanta

Top Skills'' Details

Cloud Architecture & Automation: 10+ years of experience designing and deploying cloud infrastructure using Google Cloud Platform (preferred), Azure, or Databricks with strong Terraform/Bicep expertise.

DevSecOps & Governance: Proven ability to implement secure CI/CD pipelines, cloud security controls (IAM, encryption, secrets management), and governance frameworks.

AI/ML Operations & Observability: Hands-on experience supporting production AI/ML environments with model monitoring, drift detection, logging, alerting, and observability solutions

Job Description

We are seeking a Senior DevOps Engineer IV to support the design, implementation, and optimization of enterprise AI platforms and cloud infrastructure. This role will focus on cloud architecture, Infrastructure as Code (IaC), AI/ML operations, observability, security, governance, and Agentic AI systems. The ideal candidate will have extensive experience building scalable cloud environments, implementing DevOps best practices, and enabling production-grade AI solutions in regulated enterprise environments.

Key Responsibilities

Design, deploy, and maintain enterprise cloud infrastructure supporting AI/ML workloads.

Implement Infrastructure as Code using Terraform, Bicep, or similar automation tools.

Develop and manage CI/CD pipelines with integrated security, governance, and compliance controls.

Architect scalable, highly available AI platforms across cloud environments.

Drive FinOps practices, including cloud cost optimization, resource utilization, and enterprise cost visibility.

Implement AI observability frameworks covering model performance, drift detection, reliability, business KPIs, and operational monitoring.

Design and support AI/ML lifecycle management including monitoring, retraining strategies, logging, alerting, and incident response.

Embed security, compliance, and model risk management controls into AI development and deployment processes.

Support development and operationalization of Agentic AI solutions, including orchestration, monitoring, testing, and governance.

Establish best practices for AgentOps, model governance, and AI platform reliability

Additional Skills & Qualifications

Design and implementation of multi-cloud AI infrastructure with integrated governance and policy controls.

Experience embedding security, compliance, and governance controls directly into IaC and deployment pipelines.

Strong understanding of AI FinOps, including token optimization, cost-performance tradeoffs, and enterprise cost visibility.

Experience implementing model risk management controls, including auditability, explainability, and access governance.

Knowledge of designing AI systems for regulated environments and enforcing runtime guardrails and policy controls.

Ability to develop enterprise-wide AI observability strategies, covering model performance, data drift, bias detection, reliability, and business KPIs.

Experience implementing centralized monitoring frameworks and automated response mechanisms across AI platforms.

Exposure to LLM-based applications, AI agents, prompt engineering, API integrations, and orchestration frameworks such as LangChain.

Experience designing and supporting agent-based systems at scale, including multi-agent coordination, tool orchestration, memory management, and state management.

Knowledge of AgentOps practices, including AI deployment, testing, monitoring, iteration, and governance.

Understanding of autonomous AI system failure modes and mitigation strategies.