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Cloud Engineer Ai Jobs in Raleigh, NC (NOW HIRING)

LexisNexis

Principle AWS Cloud Engineer

Raleigh, NC · On-site

$54.25 - $72.50/hr

We use ethical and powerful generative AI solutions with a flexible approach, prioritizing the best model for each legal use case. About the Role : As a Consulting Principal AWS Cloud Engineer, you ...

LexisNexis

Principle AWS Cloud Engineer

Raleigh, NC · On-site +1

$54.25 - $72.50/hr

We use ethical and powerful generative AI solutions with a flexible approach, prioritizing the best model for each legal use case. About the Role : As a Consulting Principal AWS Cloud Engineer, you ...

Verily Life Sciences

Cloud Engineer III

Raleigh, NC · On-site

$54.25 - $72.50/hr

Who We Are Verily Health is a data platform and technology company purpose-built to power AI ... Description As a Cloud Engineer at Verily you will help us develop our cloud platform capabilities ...

Verily

Cloud Engineer III

Raleigh, NC

$54.25 - $72.50/hr

Who We Are Verily Health is a data platform and technology company purpose-built to power AI ... Description As a Cloud Engineer at Verily you will help us develop our cloud platform capabilities ...

Verily Life Sciences

Senior Cloud Engineer

Raleigh, NC · On-site

$54.25 - $72.50/hr

Who We Are Verily Health is a data platform and technology company purpose-built to power AI ... Description As a Cloud Engineer at Verily you will help us develop our cloud platform capabilities ...

LexisNexis

Principal AWS Cloud Engineer-2

Raleigh, NC · On-site +1

We use ethical and powerful generative AI solutions with a flexible approach, prioritizing the best model for each legal use case. About the Role : As a Consulting Principal AWS Cloud Engineer, you ...

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How much do cloud engineer ai jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for cloud engineer ai in Raleigh, NC is $61.13, according to ZipRecruiter salary data. Most workers in this role earn between $52.12 and $69.62 per hour, depending on experience, location, and employer.

What is a cloud engineer AI?

A Cloud Engineer AI is a technology professional who specializes in building, deploying, and maintaining artificial intelligence (AI) solutions using cloud computing platforms. They integrate AI and machine learning models into cloud environments such as AWS, Azure, or Google Cloud, ensuring scalability, security, and efficiency. Their role often involves managing cloud infrastructure, automating workflows, and optimizing resources to support AI workloads. Cloud Engineer AIs collaborate with data scientists, developers, and IT teams to deliver robust AI-powered applications and services.

What are the key skills and qualifications needed to thrive as a cloud engineer AI, and why are they important?

To thrive as a Cloud Engineer AI, you need a strong background in cloud computing, AI/ML concepts, programming (Python, Java), and a relevant degree in computer science or related field. Familiarity with cloud platforms like AWS, Azure, or Google Cloud, as well as AI/ML frameworks and certifications such as AWS Certified Machine Learning or Google Professional Machine Learning Engineer, is essential. Effective problem-solving, collaboration, and adaptability are crucial soft skills that help manage evolving technologies and cross-functional teamwork. These skills and qualifications ensure robust, scalable AI solutions are developed and maintained efficiently in cloud environments.

What are some common challenges cloud engineers specializing in AI face when deploying machine learning models in production environments?

Cloud Engineers focusing on AI often encounter challenges such as ensuring scalable infrastructure for demanding workloads, maintaining data security and compliance, and optimizing model performance in distributed systems. Managing resource allocation to balance cost and efficiency while deploying machine learning models can be complex, especially when dealing with large datasets and real-time processing. Additionally, close collaboration with data scientists and DevOps teams is essential to streamline model deployment and monitoring, making strong communication and cross-disciplinary skills valuable in this role.

How much do cloud engineer AI make?

The average salary for a Cloud Engineer specializing in AI ranges from $100,000 to $150,000 annually, depending on experience, certifications, and location. Skilled professionals with expertise in cloud platforms like AWS, Azure, or Google Cloud and knowledge of AI tools can earn higher salaries, especially in senior roles or specialized environments.

What does a cloud engineer AI do?

A cloud engineer AI designs, develops, and manages cloud-based infrastructure and AI solutions. They work with cloud platforms like AWS, Azure, or Google Cloud, and often utilize tools such as containerization and automation to deploy scalable AI applications. Strong knowledge of machine learning, programming, and cloud security is essential for this role.

Will AI take cloud engineer jobs?

AI is transforming cloud engineering by automating tasks such as infrastructure management, deployment, and monitoring. However, cloud engineers are needed to design, implement, and oversee AI-driven systems, making their expertise essential for integrating AI tools effectively into cloud environments.
Infographic showing various Cloud Engineer Ai job openings in Raleigh, NC as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $127,150 per year, or $61.1 per hour.

Principle AWS Cloud Engineer

Raleigh, NC • On-site

LexisNexis
IT Services • 10K+ employees
Learn more about LexisNexisexternal

$54.25 - $72.50/hr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 days ago

LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

195th of 501 rated business services

Job description

** Please note that Raleigh, NC would be the preferred location for this role. We are open to hiring on a remote basis in the United States, with the understanding that the selected individual will work a U.S. eastern time zone schedule. **
About Our Team:
LexisNexis Legal & Professional serves customers in over 150 countries with 11,800 employees globally. We are part of RELX, a provider of information-based analytics and decision tools for professional and business customers. Our company leads in deploying AI and advanced technologies to the legal market, enhancing productivity and transforming the business and practice of law. We use ethical and powerful generative AI solutions with a flexible approach, prioritizing the best model for each legal use case.
About the Role:
As a Consulting Principal AWS Cloud Engineer, you will design, build, and guide secure, scalable AWS cloud platforms and cloud-native solutions. You will partner with engineering, security, architecture, and product teams to implement infrastructure automation, Kubernetes and serverless patterns, observability, and resilient operating practices. This role combines hands-on cloud engineering with technical leadership, mentoring, and practical architectural guidance that supports business agility, reliability, and cost-effective innovation.
Requirements
  • 10+ years of engineering or IT experience, with 5+ years focused on AWS cloud engineering, automation, platform engineering, or cloud architecture.
  • Strong hands-on experience with core AWS services, including EC2, S3, VPC, IAM, Lambda, RDS/Aurora, EKS, CloudWatch, and Route 53.
  • Experience leveraging AI-assisted engineering tools (e.g., GitHub Copilot, Claude, Cursor) in day-to-day development, code review, and platform work - and a demonstrated ability to enable and upskill other engineers in their adoption.
  • Experience designing and implementing Infrastructure as Code using Terraform, AWS CloudFormation, AWS CDK, or similar tooling.
  • Strong scripting or programming skills using Python, Bash, Go, or similar languages to automate cloud operations and integration workflows.
  • Knowledge of CI/CD, DevOps, and GitOps practices using tools such as Jenkins, GitHub Actions, Argo CD, Azure DevOps, or comparable platforms.
  • Experience with containers and Kubernetes-based deployment patterns, including Docker, EKS, Helm, service networking, and autoscaling concepts.
  • Solid understanding of AWS networking concepts, including VPC design, subnets, routing, security groups, load balancing, DNS, and hybrid connectivity patterns.
  • Knowledge of cloud security and compliance practices, including IAM least privilege, encryption, secrets management, vulnerability remediation, and policy guardrails.
  • Experience with observability and SRE practices, including monitoring, logging, alerting, incident response, runbooks, and operational readiness reviews.
  • Experience supporting cloud data services and storage patterns such as RDS/Aurora, DynamoDB, S3, caching, backup, and lifecycle management.
  • Strong communication, collaboration, problem-solving, and mentoring skills, with the ability to influence technical decisions across teams.
  • Experience with platform engineering Internal Developer Portal (IDE) or self-service cloud development environments that help teams design, provision, deploy, and operate cloud infrastructure through governed workflows.

Responsibilities
  • Design, build, and maintain secure, highly available AWS environments optimized for reliability, performance, scalability, and cost efficiency.
  • Implement reusable AWS infrastructure patterns across compute, networking, storage, identity, containers, serverless, and database services.
  • Develop and maintain Infrastructure as Code modules, templates, and pipelines that support consistent provisioning and deployment practices.
  • Develop and maintain internal enablement resources - playbooks, templates, workshops that accelerate team adoption of AI-assisted engineering across the engineering organization.
  • Build and support Kubernetes and container-based workloads on AWS, including EKS deployment patterns, Helm-based releases, ingress, autoscaling, and observability integrations.
  • Champion the adoption of AI-assisted engineering practices across the team, identifying high-value use cases, curating tooling, and building enablement resources that raise the engineering floor.
  • Partner with application, security, architecture, and operations teams to modernize workloads and improve cloud-native delivery practices.
  • Implement security controls and operational guardrails, including least-privilege IAM, encryption, secrets management, network segmentation, and compliance-aligned practices.
  • Improve cloud operations through monitoring, logging, alerting, incident response, runbooks, automated remediation, and continuous reliability improvements.
  • Review cloud designs and changes against AWS Well-Architected principles, internal standards, and production readiness expectations.
  • Troubleshoot complex cloud, platform, networking, deployment, and performance issues across AWS environments.
  • Mentor engineers on AWS, Kubernetes, automation, security, and platform engineering best practices while promoting continuous learning.
  • Communicate technical recommendations clearly to engineering partners, product stakeholders, security teams, and leadership.

Preferred Qualifications:
  • AWS Associate or Professional-level certification, Certified Kubernetes Administrator, or comparable cloud/platform certification.
  • Experience building reusable Infrastructure as Code modules, golden paths, templates, or self-service provisioning patterns for engineering teams.
  • Experience with AWS multi-account, landing zone, or account governance patterns using services such as AWS Organizations, Control Tower, IAM Identity Center, or related guardrail capabilities.
  • Experience with serverless and event-driven AWS architectures using services such as Lambda, Step Functions, API Gateway, EventBridge, SQS, SNS, or Kinesis.
  • Experience with observability platforms and operational tooling such as CloudWatch, OpenTelemetry, Datadog, Splunk, or comparable monitoring and logging solutions.
  • Familiarity with cloud cost optimization, capacity planning, tagging strategies, and FinOps practices.
  • Experience supporting data, analytics, AI, or machine learning workloads on AWS is a plus.
  • Experience with AWS AI/ML services including Bedrock, SageMaker, or related managed AI services - particularly in designing the infrastructure and operational patterns that support AI workload deployment at scale.

Work in a way that works for you
We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous well-being initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
Working for you
We know that your well-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
  • Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits
  • Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
  • Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs
  • Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
  • Family Benefits, including bonding and family care leaves, adoption, and surrogacy benefits
  • Health Savings, Health Care, Dependent Care and Commuter Spending Accounts
  • Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice

About the Business
LexisNexis Legal & Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services.
#AIFluency
U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates.This job is eligible for an annual incentive bonus.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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