Software Engineer AI Jobs in North Carolina
Software Engineer AI jobs in North Carolina are in strong and growing demand, concentrated in technology, fintech, advanced manufacturing, and research-driven industries that make the state one of the Southeast's most active markets for this role, with openings from entry-level through senior and staff positions. The heaviest hiring is in the Research Triangle area, Charlotte, and Raleigh-Durham, where employers like Red Hat, Fidelity Investments, and Lenovo have established engineering hubs. The most sought-after specialties are machine learning systems, natural language processing, and AI infrastructure engineering. Find a role that fits below and apply directly.
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Showing 5 of 12+ Software Engineer AI 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 Software Engineer AI Jobs in North Carolina
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Find Software Engineer AI JobsSoftware Engineer AI Jobs by City in North Carolina
Where North Carolina roles are concentrated, by current openings.
Software Engineer AI 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 software engineer AI jobs across North Carolina.
- Bachelor's or master's degree in computer science, machine learning, or a related field
- Proficiency in Python, with hands-on experience building or deploying ML models
- Experience with deep learning frameworks such as PyTorch or TensorFlow
- Familiarity with cloud platforms, particularly AWS, Azure, or Google Cloud
- Strong understanding of data pipelines, model evaluation, and experiment tracking
- Ability to collaborate with cross-functional teams including data scientists and product engineers
Software Engineer AI Jobs in North Carolina: Frequently Asked Questions
How do you become a software engineer ai in North Carolina?
A bachelor's degree in computer science, data science, or a closely related field is the standard entry point for software engineer ai roles in North Carolina, and no state-issued license is required. Most North Carolina employers expect demonstrated experience with machine learning tools and applied AI projects, which candidates typically build through university programs at NC State, UNC-Chapel Hill, or Duke, followed by internships or research roles at companies in the Research Triangle or Charlotte tech corridor.
How much do software engineer AIs make in North Carolina?
Software engineer AIs 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 software engineer ais in North Carolina?
Employers hiring software engineer ais 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 fintech firms in Charlotte, enterprise software companies in the Research Triangle, and manufacturing technology operations across the Piedmont region gives this role a broad set of industries to target.
Which North Carolina cities have the most software engineer ai jobs?
Charlotte, Raleigh, and Morrisville have the most software engineer ai openings in North Carolina. Raleigh and Durham dominate because the Research Triangle anchors a dense cluster of technology companies, university spinoffs, and enterprise software employers, while Charlotte draws AI engineering roles from its large financial services and fintech sector, and cities like Cary and Morrisville add volume through established corporate campuses just outside the Triangle.
Are there remote software engineer ai jobs in North Carolina?
Yes, and more than most fields. About 67% of software engineer ai openings tied to North Carolina are remote or hybrid as of September 2026, reflecting how well-suited this work is to distributed environments. The roles most commonly offered fully remote are those focused on model development, research, and MLOps, while positions involving embedded systems or on-site infrastructure tend to require in-person presence.
How can I get hired as a software engineer ai in North Carolina with little or no experience?
The most realistic entry path is through a junior or associate AI engineer role or a machine learning internship at one of the large North Carolina employers in the Research Triangle. Companies like SAS Institute and IBM's North Carolina offices run graduate and new-hire programs that consider candidates with strong project portfolios even without prior full-time experience. Building a public GitHub portfolio with applied ML projects and completing a relevant certification in deep learning or cloud AI services gives candidates a meaningful edge when applying to these entry-level programs.
Where can I find and apply to software engineer ai jobs in North Carolina?
You can find and apply to software engineer ai jobs in North Carolina on Migrate Mate, which lists current North Carolina openings across industries and experience levels. Search the available roles, find one that fits your background and target location, and apply directly.
See All 12 Software Engineer AI Jobs in North Carolina
Find roles in North Carolina that match your experience and apply in just a few clicks.
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