Senior AI Software Engineer Jobs in North Carolina
Senior AI Software Engineer jobs in North Carolina are among the most actively recruited technology positions in the state, concentrated in enterprise software, life sciences, financial services, and defense contracting, with demand at every level from mid-career engineers through principal-level architects. The heaviest hiring is in the Research Triangle area of Raleigh, Durham, and Chapel Hill, along with Charlotte and Cary, where established employers like Red Hat, SAS Institute, and Lenovo maintain significant engineering operations. The most in-demand specialties include large language model development, MLOps infrastructure, and AI-driven data platform engineering. Find a role that fits below and apply directly.
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Showing 5 of 12+ Senior AI Software Engineer jobs
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 12 Senior AI Software Engineer Jobs in North Carolina
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Find JobsSenior AI Software Engineer Jobs by City in North Carolina
Where North Carolina roles are concentrated, by current openings.
Senior AI Software Engineer Job Market in North Carolina
A snapshot from current North Carolina openings, updated as new roles post.
Who's Hiring
What North Carolina Employers Look For
The qualifications that appear most often in senior AI software engineer jobs across North Carolina.
- Bachelor's or master's degree in computer science, artificial intelligence, or a related engineering field
- Demonstrated experience designing and deploying machine learning models in production environments
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience with cloud platforms including AWS, Azure, or Google Cloud for AI workloads
- Strong background in MLOps practices including model monitoring, versioning, and CI/CD pipelines
- Ability to collaborate cross-functionally with data scientists, product managers, and platform engineers
Senior AI Software Engineer Jobs in North Carolina: Frequently Asked Questions
How do you become a senior ai software engineer in North Carolina?
Becoming a senior ai software engineer in North Carolina typically requires a bachelor's or master's degree in computer science, data science, or a closely related field, followed by several years of hands-on experience building and deploying AI systems. North Carolina does not require a state-issued license for this role. Employers in the Research Triangle and Charlotte corridors place strong weight on demonstrated production ML experience, published work, or open-source contributions alongside formal credentials.
How much do senior AI software engineers make in North Carolina?
Senior AI software engineers in North Carolina earn a median of about $134,710 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $83,840 for the lowest 10% to over $179,310 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire senior ai software engineers in North Carolina?
Employers hiring senior ai software engineers in North Carolina right now include AT&T, Humana, and Lenovo, based on current listings on Migrate Mate as of September 2026. North Carolina's concentration of research universities and major technology campuses, particularly around the Research Triangle Park, makes the state an ongoing destination for companies scaling AI engineering teams.
Which North Carolina cities have the most senior ai software engineer jobs?
The cities with the most senior ai software engineer openings in North Carolina are Charlotte, Raleigh, and Morrisville. The Research Triangle area anchors most of this demand, driven by the dense cluster of technology companies, life sciences firms, and research institutions in and around Raleigh, Durham, and Chapel Hill, while Charlotte generates significant openings through its large financial services and enterprise technology employers.
Are there remote senior ai software engineer jobs in North Carolina?
Yes, and more than most fields. About 67% of senior ai software engineer openings tied to North Carolina are remote or hybrid as of September 2026, reflecting how broadly AI engineering work translates to distributed teams. Model research, experimentation, and pipeline development are the parts of the role most commonly offered fully remotely, while on-site expectations tend to concentrate around collaborative sprint work and stakeholder integration.
How can I get hired as a senior ai software engineer in North Carolina with little or no experience?
The most realistic entry path is building a portfolio of end-to-end machine learning projects and targeting associate or junior AI engineer roles at North Carolina technology companies before moving into senior positions. Employers such as SAS Institute and IBM's Research Triangle Park operations have historically run new-grad and rotational programs for early-career engineers. Transitioning from a data analyst, software developer, or data engineer role is a common lateral move that opens doors, and completing a recognized graduate certificate in machine learning strengthens candidacy significantly.
Where can I find and apply to senior ai software engineer jobs in North Carolina?
You can find and apply to senior ai software engineer jobs in North Carolina on Migrate Mate, which lists current openings tied to the state. Find roles that fit your experience and apply directly to the ones that match.
See All 12 Senior AI Software 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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