AI Platform Engineer Jobs in North Carolina
AI Platform Engineer jobs in North Carolina are in strong demand, concentrated in the technology, financial services, and life sciences sectors, with openings at every level from entry-level ML infrastructure roles through principal and staff engineer positions. Raleigh-Durham, Charlotte, and the Research Triangle Park corridor account for the largest share of hiring, anchored by employers such as Red Hat, Lenovo, and Bank of America. The most sought-after specialties in North Carolina include MLOps pipeline development, large language model deployment infrastructure, and cloud-native AI tooling on AWS and Azure. Find a role that fits below and apply directly.
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Company Summary
Targeted Approach is an ISO 9001:2015-certified Service-Disabled Veteran-Owned Small Business (SDVOSB) providing technical, analytical, logistics, management, and mission support services to customers across the Department of Defense and Federal Government.
Targeted Approach is an Equal Opportunity Employer. Employment decisions are based on qualifications, merit, and mission requirements without regard to legally protected characteristics.
Position Summary
Targeted Approach (TA) is seeking an Intermediate Artificial Intelligence (AI) Engineer to support a Department of Defense program at Marine Corps Air Station (MCAS) Cherry Point, North Carolina. The Intermediate AI Engineer will provide hands-on technical expertise in artificial intelligence engineering, machine learning model development, cloud engineering, systems deployment, automation, security compliance, performance monitoring, quality assurance, and technical support.
The successful candidate will bridge data science, artificial intelligence, cloud technologies, and software engineering to design, develop, test, deploy, and sustain production-ready AI/ML solutions. This position will support the transition of AI capabilities from development and experimentation into reliable, secure, and scalable operational environments.
Duties
- Design, build, test, evaluate, and deploy machine learning models and artificial intelligence applications that automate tasks, improve business and operational processes, and address complex technical problems.
- Apply data science and software engineering principles to develop production-ready AI/ML systems capable of operating reliably within DoD environments.
- Develop and maintain software, scripts, data pipelines, and AI/ML solutions using Python, SQL, and other applicable programming and query languages.
- Develop AI/ML solutions using frameworks and libraries such as TensorFlow, PyTorch, or comparable technologies.
- Design, build, configure, and deploy AI applications and supporting infrastructure within cloud environments such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), or similar platforms.
- Design, build, configure, and maintain virtualized and cloud-based systems supporting organizational data, applications, AI capabilities, and infrastructure.
- Support the migration and modernization of on-premises applications, data, and systems to cloud-based environments.
- Develop and implement automation for cloud infrastructure, data pipelines, AI/ML workflows, deployment processes, and recurring technical activities to improve efficiency, scalability, repeatability, and reliability.
- Support applicable DoD cybersecurity, information assurance, and security compliance requirements for AI, cloud, and virtualized environments.
- Monitor AI models, applications, systems, and cloud environments to evaluate performance, scalability, reliability, availability, and operational effectiveness.
- Troubleshoot technical issues associated with AI/ML applications, cloud environments, data pipelines, interfaces, and deployed systems.
- Perform testing, validation, documentation, configuration management, and quality assurance activities throughout the AI/ML development and deployment lifecycle.
- Collaborate with data analysts, software developers, cloud engineers, cybersecurity personnel, Government stakeholders, and other technical SMEs to translate operational requirements into effective technical solutions.
- Develop and maintain technical documentation supporting system architecture, AI/ML models, cloud configurations, interfaces, deployment procedures, automation, testing, and sustainment.
Experience
- Demonstrated experience designing, building, testing, and deploying machine learning models and artificial intelligence applications.
- Experience integrating data science and software engineering concepts to create production-ready AI systems.
- Experience programming and querying using Python and SQL.
- Experience using AI/ML frameworks such as TensorFlow, PyTorch, or similar tools.
- Experience designing, building, and deploying AI systems within AWS, Azure, GCP, or comparable cloud platforms.
- Experience designing, building, and maintaining virtualized and cloud-based environments supporting enterprise data, applications, and infrastructure.
- Experience supporting the migration of on-premises systems and applications to cloud environments.
- Experience automating cloud, infrastructure, data, and AI/ML processes.
- Experience supporting cybersecurity and security compliance requirements applicable to AI, cloud, and virtualized environments.
- Experience monitoring and optimizing system, model, application, and cloud performance to support scalability, reliability, and operational effectiveness.
Education Requirements
No degree requires 12 years of general experience
Associate's degree requires 8 years of general experience
Bachelor's degree 7 years of general experience
Master's degree 6 years of general experience
Ph.D. 4 years of general experience
Relevant degrees may include Artificial Intelligence, Machine Learning, Computer Science, Data Science, Software Engineering, Computer Engineering, Information Technology, Information Systems, or another related technical discipline.
Preferred Qualifications
- MLOps and AI/ML lifecycle management.
- DevSecOps and CI/CD pipelines.
- Infrastructure as Code (IaC) and automated cloud provisioning.
- Docker, Kubernetes, or other containerization/orchestration technologies.
- Cloud-native data storage, processing, and analytics services.
- REST APIs and integration of AI/ML capabilities with enterprise applications.
- Model versioning, validation, monitoring, retraining, and performance optimization.
- Git or comparable source-code/configuration management tools.
- DoD cloud environments and cloud security requirements.
- Risk Management Framework (RMF), Security Technical Implementation Guides (STIGs), or other DoD cybersecurity requirements.
- Working within DoD, Department of the Navy, or U.S. Marine Corps technical environments.
- Supporting AI/ML capabilities through development, testing, deployment, operation, and sustainment
Join us if you’re passionate about harnessing the power of artificial intelligence to transform data into impactful insights! We value innovative thinkers eager to develop next-generation AI models that shape the future of technology-driven solutions.
Pay: $110,000.00 - $130,000.00 per year
Benefits:
- 401(k) matching
- Dental insurance
- Health insurance
- Life insurance
- Paid time off
- Referral program
- Vision insurance
Education:
- Bachelor's (Preferred)
Experience:
- AI/ ML solutions: 7 years (Required)
Security clearance:
- Secret (Required)
Ability to Commute:
- Cherry Point, NC 28533 (Required)
Work Location: In person
Company Summary
Targeted Approach is an ISO 9001:2015-certified Service-Disabled Veteran-Owned Small Business (SDVOSB) providing technical, analytical, logistics, management, and mission support services to customers across the Department of Defense and Federal Government.
Targeted Approach is an Equal Opportunity Employer. Employment decisions are based on qualifications, merit, and mission requirements without regard to legally protected characteristics.
Position Summary
Targeted Approach (TA) is seeking an Intermediate Artificial Intelligence (AI) Engineer to support a Department of Defense program at Marine Corps Air Station (MCAS) Cherry Point, North Carolina. The Intermediate AI Engineer will provide hands-on technical expertise in artificial intelligence engineering, machine learning model development, cloud engineering, systems deployment, automation, security compliance, performance monitoring, quality assurance, and technical support.
The successful candidate will bridge data science, artificial intelligence, cloud technologies, and software engineering to design, develop, test, deploy, and sustain production-ready AI/ML solutions. This position will support the transition of AI capabilities from development and experimentation into reliable, secure, and scalable operational environments.
Duties
- Design, build, test, evaluate, and deploy machine learning models and artificial intelligence applications that automate tasks, improve business and operational processes, and address complex technical problems.
- Apply data science and software engineering principles to develop production-ready AI/ML systems capable of operating reliably within DoD environments.
- Develop and maintain software, scripts, data pipelines, and AI/ML solutions using Python, SQL, and other applicable programming and query languages.
- Develop AI/ML solutions using frameworks and libraries such as TensorFlow, PyTorch, or comparable technologies.
- Design, build, configure, and deploy AI applications and supporting infrastructure within cloud environments such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), or similar platforms.
- Design, build, configure, and maintain virtualized and cloud-based systems supporting organizational data, applications, AI capabilities, and infrastructure.
- Support the migration and modernization of on-premises applications, data, and systems to cloud-based environments.
- Develop and implement automation for cloud infrastructure, data pipelines, AI/ML workflows, deployment processes, and recurring technical activities to improve efficiency, scalability, repeatability, and reliability.
- Support applicable DoD cybersecurity, information assurance, and security compliance requirements for AI, cloud, and virtualized environments.
- Monitor AI models, applications, systems, and cloud environments to evaluate performance, scalability, reliability, availability, and operational effectiveness.
- Troubleshoot technical issues associated with AI/ML applications, cloud environments, data pipelines, interfaces, and deployed systems.
- Perform testing, validation, documentation, configuration management, and quality assurance activities throughout the AI/ML development and deployment lifecycle.
- Collaborate with data analysts, software developers, cloud engineers, cybersecurity personnel, Government stakeholders, and other technical SMEs to translate operational requirements into effective technical solutions.
- Develop and maintain technical documentation supporting system architecture, AI/ML models, cloud configurations, interfaces, deployment procedures, automation, testing, and sustainment.
Experience
- Demonstrated experience designing, building, testing, and deploying machine learning models and artificial intelligence applications.
- Experience integrating data science and software engineering concepts to create production-ready AI systems.
- Experience programming and querying using Python and SQL.
- Experience using AI/ML frameworks such as TensorFlow, PyTorch, or similar tools.
- Experience designing, building, and deploying AI systems within AWS, Azure, GCP, or comparable cloud platforms.
- Experience designing, building, and maintaining virtualized and cloud-based environments supporting enterprise data, applications, and infrastructure.
- Experience supporting the migration of on-premises systems and applications to cloud environments.
- Experience automating cloud, infrastructure, data, and AI/ML processes.
- Experience supporting cybersecurity and security compliance requirements applicable to AI, cloud, and virtualized environments.
- Experience monitoring and optimizing system, model, application, and cloud performance to support scalability, reliability, and operational effectiveness.
Education Requirements
No degree requires 12 years of general experience
Associate's degree requires 8 years of general experience
Bachelor's degree 7 years of general experience
Master's degree 6 years of general experience
Ph.D. 4 years of general experience
Relevant degrees may include Artificial Intelligence, Machine Learning, Computer Science, Data Science, Software Engineering, Computer Engineering, Information Technology, Information Systems, or another related technical discipline.
Preferred Qualifications
- MLOps and AI/ML lifecycle management.
- DevSecOps and CI/CD pipelines.
- Infrastructure as Code (IaC) and automated cloud provisioning.
- Docker, Kubernetes, or other containerization/orchestration technologies.
- Cloud-native data storage, processing, and analytics services.
- REST APIs and integration of AI/ML capabilities with enterprise applications.
- Model versioning, validation, monitoring, retraining, and performance optimization.
- Git or comparable source-code/configuration management tools.
- DoD cloud environments and cloud security requirements.
- Risk Management Framework (RMF), Security Technical Implementation Guides (STIGs), or other DoD cybersecurity requirements.
- Working within DoD, Department of the Navy, or U.S. Marine Corps technical environments.
- Supporting AI/ML capabilities through development, testing, deployment, operation, and sustainment
Join us if you’re passionate about harnessing the power of artificial intelligence to transform data into impactful insights! We value innovative thinkers eager to develop next-generation AI models that shape the future of technology-driven solutions.
Pay: $110,000.00 - $130,000.00 per year
Benefits:
- 401(k) matching
- Dental insurance
- Health insurance
- Life insurance
- Paid time off
- Referral program
- Vision insurance
Education:
- Bachelor's (Preferred)
Experience:
- AI/ ML solutions: 7 years (Required)
Security clearance:
- Secret (Required)
Ability to Commute:
- Cherry Point, NC 28533 (Required)
Work Location: In person
See All 23 AI Platform Engineer Jobs in North Carolina
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Find AI Platform Engineer JobsAI Platform Engineer Jobs by City in North Carolina
Where North Carolina roles are concentrated, by current openings.
AI Platform Engineer Job Market in North Carolina
A snapshot from current North Carolina openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Banking & Financial Services
- Consulting & Professional Services
What North Carolina Employers Look For
The qualifications that appear most often in AI platform engineer jobs across North Carolina.
- Bachelor's or master's degree in computer science, data engineering, or a related technical field
- Hands-on experience building and maintaining ML pipelines and model deployment infrastructure
- Proficiency with cloud platforms such as AWS SageMaker, Azure Machine Learning, or Google Vertex AI
- Strong programming skills in Python with experience in orchestration tools like Kubeflow or Apache Airflow
- Familiarity with containerization and Kubernetes for scalable AI workload management
- Experience integrating CI/CD practices into machine learning workflows using tools like MLflow or DVC
AI Platform Engineer Jobs in North Carolina: Frequently Asked Questions
How do you become a ai platform engineer in North Carolina?
AI platform engineer roles in North Carolina do not require a state-issued license or credential. Most employers in the Research Triangle and Charlotte markets hire candidates with a bachelor's degree in computer science, software engineering, or a related field, combined with demonstrated experience in cloud infrastructure and ML tooling. Building a portfolio of deployed ML pipelines, contributing to open-source MLOps projects, and earning cloud certifications from AWS or Azure strengthens candidacy considerably with North Carolina employers.
How much do AI platform engineers make in North Carolina?
AI platform engineers in North Carolina earn a median of about $104,850 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $39,190 for the lowest 10% to over $175,660 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai platform engineers in North Carolina?
Employers hiring ai platform engineers in North Carolina right now include Lenovo, AT&T, and Sysdig, based on current listings on Migrate Mate as of September 2026. North Carolina's concentration of technology companies in the Research Triangle Park area and major financial institutions headquartered in Charlotte makes the state one of the more active markets for this role in the Southeast.
Which North Carolina cities have the most ai platform engineer jobs?
Charlotte, Morrisville, and Raleigh have the most ai platform engineer openings in North Carolina. Raleigh and Durham dominate because of the dense cluster of technology companies, research universities, and life sciences firms in and around Research Triangle Park, while Charlotte's large financial services and fintech sector drives consistent demand for AI infrastructure talent in that metro.
Are there remote ai platform engineer jobs in North Carolina?
Yes, and more than most fields. AI platform engineering is largely cloud-based and tooling-focused work, making it well-suited to remote arrangements. About 53% of ai platform engineer openings tied to North Carolina are remote or hybrid as of September 2026, reflecting employer flexibility in this discipline. Infrastructure design, pipeline development, and model monitoring tasks are the functions most commonly performed fully remote.
How can I get hired as a ai platform engineer in North Carolina with little or no experience?
The most realistic entry path is joining a North Carolina technology company or large enterprise as a data or software engineer and transitioning into AI platform work once you have exposure to ML workflows. Companies in the Research Triangle Park ecosystem and Charlotte's fintech sector regularly hire new graduates into infrastructure or cloud engineering associate roles that overlap with AI platform responsibilities. Building a portfolio of end-to-end MLOps projects using open-source tools and earning an AWS or Azure cloud practitioner certification gives candidates a concrete edge when applying to these teams.
Where can I find and apply to ai platform engineer jobs in North Carolina?
You can find and apply to ai platform engineer jobs in North Carolina on Migrate Mate, which lists current openings across the state. Search the roles available, find the positions that fit your background and location preference, and apply directly to the ones that match.
See All 23 AI Platform Engineer Jobs in North Carolina
Find roles in North Carolina that match your experience and apply in just a few clicks.
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