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

ARA

Senior AI Systems Engineer

Raleigh, NC · On-site

$92K - $126K/yr

Lead the deployment, integration, and operational support of AI platforms, tools, and services ... Proficiency with DevOps and MLOps practices, including CI/CD pipelines, Git-based workflows ...

Compunnel

Machine Learning Engineer Lead

Raleigh, NC · On-site

$99K - $131K/yr

The role will shape long-term AI platform strategy, establish technical standards, and mentor engineering teams while supporting highly available, secure, and scalable AI systems. Key ...

Lenovo

Software Engineer -- AI Experiences

Morrisville, NC · On-site

$125 - $140/hr

Description and Requirements About Our Team Lenovo is building Qira, a next-generation hybrid AI platform that spans Windows, Android, and cloud. We are hiring a Staff Engineer to drive the technical ...

First Citizens

Principal AI Architect

Raleigh, NC · On-site

$160 - $240/hr

AI Platform Engineering & MLOps * Prototype and operationalize advanced AI solutions, including GenAI and LLM‑based systems. Architect end‑to‑end MLOps capabilities, including model lifecycle ...

GEI Consultants

AI Engineer

Cary, NC · On-site

$110K - $150K/yr

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... This role works closely with solution architects and platform teams to ensure AI solutions are ...

GEI Consultants

AI Engineer

Cary, NC · On-site

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... This role works closely with solution architects and platform teams to ensure AI solutions are ...

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All JobsAi Platform Engineer JobsAi Platform Engineer Jobs in Raleigh, NC

Ai Platform Engineer information

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How much do ai platform engineer jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for ai platform engineer in Raleigh, NC is $62.17, according to ZipRecruiter salary data. Most workers in this role earn between $49.09 and $71.73 per hour, depending on experience, location, and employer.

What is an AI Platform Engineer?

AI Platform Engineers are technology professionals who design, build, and maintain the infrastructure that supports the development, deployment, and scaling of artificial intelligence (AI) and machine learning (ML) models. They work closely with data scientists and software engineers to ensure that AI solutions can run efficiently and securely in production environments. Their responsibilities often include managing cloud or on-premises platforms, automating workflows, and implementing best practices for model versioning, monitoring, and resource optimization.

How does an AI Platform Engineer typically collaborate with data scientists and software engineers in a project environment?

AI Platform Engineers often serve as a bridge between data scientists and software engineers, ensuring that machine learning models are seamlessly integrated into scalable, production-ready systems. They work closely with data scientists to understand model requirements and deployment needs, and with software engineers to embed these models within applications and services. This collaboration involves frequent communication, joint troubleshooting, and participation in code reviews to maintain a robust and efficient AI infrastructure.

What are the key skills and qualifications needed to thrive as an AI Platform Engineer, and why are they important?

To thrive as an AI Platform Engineer, you need strong programming skills (especially in Python and Java), a background in computer science or related fields, and experience with machine learning frameworks. Familiarity with cloud platforms (like AWS, Azure, or GCP), containerization tools (Docker, Kubernetes), and CI/CD systems is typically required, along with certifications such as Google Cloud Professional Machine Learning Engineer. Excellent problem-solving, collaboration, and communication skills help you integrate AI solutions across teams and projects. These competencies ensure the efficient development, deployment, and maintenance of scalable AI systems in dynamic production environments.

What is the difference between Ai Platform Engineer vs Data Engineer?

AspectAi Platform EngineerData Engineer
CredentialsBachelor's in CS, AI, or related; experience with cloud platformsBachelor's in CS, Data Science, or related; experience with databases and ETL tools
Work EnvironmentDeveloping AI infrastructure, deploying ML models, working with cloud servicesBuilding data pipelines, managing data storage, ensuring data quality
Industry UsageTech companies, AI startups, cloud providersFinance, healthcare, e-commerce, any data-driven industry

While both roles involve working with data and cloud platforms, Ai Platform Engineers focus on building and maintaining AI infrastructure and deploying machine learning models. Data Engineers primarily develop data pipelines and manage data storage. The roles often collaborate but serve different core functions within AI and data ecosystems.

How to become an AI platform engineer?

To become an AI platform engineer, you should have a strong background in computer science, software engineering, or related fields, with expertise in machine learning frameworks, cloud computing, and programming languages like Python or Java. Gaining experience with AI tools, data management, and infrastructure deployment is essential, often supported by certifications in cloud platforms such as AWS or Azure. Building a portfolio of projects and staying updated on AI and DevOps practices can also enhance your qualifications.

What does an AI platform engineer do?

An AI platform engineer designs, develops, and maintains the infrastructure and tools needed to deploy and manage artificial intelligence models at scale. They work with cloud services, programming languages, and machine learning frameworks to ensure efficient model training, deployment, and monitoring in production environments.

What is the salary of AI platform engineer?

The salary of an AI platform engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and machine learning may earn higher compensation.

What are popular job titles related to Ai Platform Engineer jobs in Raleigh, NC?

For Ai Platform Engineer jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Ai Platform Engineer jobs in Raleigh, NC look for?

The top searched job categories for Ai Platform Engineer jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Ai Platform Engineer jobs?

Cities near Raleigh, NC with the most Ai Platform Engineer job openings:

Ai Platform Engineer jobs near you
Infographic showing various Ai Platform Engineer job openings in Raleigh, NC as of August 2026, with employment types broken down into 57% Full Time, 40% Part Time, and 3% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $129,312 per year, or $62.2 per hour.

Senior AI Systems Engineer

ARA

Raleigh, NC • On-site

$92K - $126K/yr

Full-time

Re-posted 21 days ago

Job description

Essential Functions:
  • Lead the deployment, integration, and operational support of AI platforms, tools, and services, ensuring compatibility with existing systems and enterprise processes.
  • Design, implement, monitor, and optimize AI infrastructure, working with server, cloud, and platform engineering teams.
  • Operationalize machine learning workflows and support AI-enabled applications from development through production deployment and sustainment.
  • Build and maintain CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback, and lifecycle management.
  • Implement infrastructure automation using scripting, Infrastructure as Code, and configuration management practices.
  • Provide ongoing technical support, troubleshooting, root cause analysis, and documentation for AI platforms and user-facing AI services.
  • Maintain observability across AI systems through logging, metrics, performance monitoring, alerting, and incident response practices.
  • Ensure security, compliance, and governance requirements are met, including participation in audits, vulnerability management, and secure architecture reviews.
  • Assess and implement system enhancements to improve performance, scalability, reliability, and cost efficiency.
  • Collaborate across divisions to support diverse AI initiatives and align technical implementations with mission and business objectives.
  • Evaluate emerging AI tools, frameworks, and infrastructure approaches for operational fit, supportability, and long-term value.
  • Develop and maintain technical documentation, runbooks, architecture diagrams, and operational procedures.

Experience and Skills Required:
  • Bachelor's degree in computer science, Engineering, Information Technology, or a related STEM field with 8-10 years of engineering experience.
  • 2+ years of experience supporting AI/ML platforms, MLOps workflows, model deployment, or AI-enabled infrastructure.
  • Strong coding and automation skills in Python, Bash, or similar scripting languages.
  • Experience with AI/ML frameworks and tooling such as PyTorch, Hugging Face, or similar ecosystems.
  • Proficiency with DevOps and MLOps practices, including CI/CD pipelines, Git-based workflows, containerization, and Kubernetes.
  • Experience deploying AI/ML models or AI services into operational environments, including containerized, cloud, or high-performance computing environments.
  • Familiarity with security frameworks and compliance standards such as NIST and CMMC.
  • Familiarity with AI security functionality in enterprise environments including OAuth
  • Strong communication skills and the ability to collaborate effectively across technical and non-technical teams.

Preferred:
  • Advanced degree or certifications related to AI or machine learning.
  • Experience integrating AI models into scientific workflows.
  • Familiarity with large language model (LLM) APIs and orchestration frameworks such as OpenAI, Hugging Face, LangGraph, or LangChain.
  • Experience with model serving, inference optimization, or AI platform tools such as MLflow, Kubeflow, vLLM, or similar.
  • Experience with simulations for scientific or engineering projects, particularly physical systems simulations.
  • Experience with GPU-based systems or running AI models in HPC environments.
  • Experience writing and deploying MCP Servers on Kubernetes
  • DoD experience
  • Secret Security Clearance - Active or Inactive

Education:
  • Bachelor's degree in CS, Software Engineering or other IT-related field or equivalent experience

REMOTE WORK NOTICE: This position may be performed fully remote, hybrid, or onsite at an ARA office. Preference will be given to candidates located onsite in the Albuquerque, NM and Raleigh, NC area.
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.

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