> Markdown version of [/jobs/ext/3825408-intermediate-ai-engineer](https://www.wearedevelopers.com/jobs/ext/3825408-intermediate-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Intermediate AI Engineer - **Company:** Nlogic, Inc. - **Location:** Charlotte, NC, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Engineering, Computer Programming, Data Systems, Python (Programming Language), Machine Learning, Cloud Services, Tensorflow, Standard Sql, Software Engineering, SQL Databases, Google Cloud, Cloud Platform System, Pytorch, Containerization, Kubernetes, Infrastructure Automation Frameworks, Machine Learning Operations, Docker - **Published:** October 18, 2026 - **Apply:** https://www.dice.com/job-detail/3ecd21cd-e7ba-4fa0-b91b-db1d172497dd ## About the Role * Active, in-scope Secret security clearance or the ability to obtain and maintain a Secret security clearance required., + Bachelor's degree in a STEM-related field and 8 years of relevant experience; or + Master's degree in a STEM-related field and 6 years of relevant experience; or + PhD in a STEM-related field and 4 years of relevant experience; or + Associate degree and 7 years of relevant experience; or + High school diploma and 12 years of relevant experience. * Experience developing and deploying machine learning models and AI applications * Experience bridging software engineering and data science concepts * Experience programming with Python and SQL * Experience using machine learning frameworks such as TensorFlow, PyTorch, or equivalent technologies * Experience supporting cloud platforms including AWS, Azure, Google Cloud Platform, or similar environments * Experience supporting virtualized and cloud-based systems.Experience supporting cloud migration initiatives * Experience automating infrastructure, AI, and data workflows * Experience supporting security compliance requirements * Experience monitoring AI systems and cloud performance. Preferred Qualifications * Experience deploying machine learning models into production environments * Experience supporting MLOps or AI operationalization efforts * Experience with containerization technologies such as Docker or Kubernetes * Cloud platform certifications.Experience supporting Department of Defense or Federal Government programs Position Details * Work Model: Full-Time, Onsite in Cherry Point, NC * Travel: Occasional travel may be required in support of customer requirements * Work Hours: Standard work hours * U.S. Citizenship is required * Active U.S. Secret security clearance required (or ability to obtain and maintain) ## Description nLogic is seeking an Intermediate AI Engineer to support anticipated work on a mission-focused effort in the Cherry Point area. This role will play a key part in supporting artificial intelligence, machine learning, cloud engineering, and automation initiatives within a collaborative defense and technology environment. In this role, you will work closely with engineers, developers, data professionals, and government stakeholders to develop, deploy, and maintain AI-enabled solutions that improve mission effectiveness, operational efficiency, and data-driven decision-making. Responsibilities * Develop, test, deploy, and maintain machine learning models and artificial intelligence applications * Support the development of production-ready AI systems * Develop software and data solutions using Python, SQL, and related technologies * Utilize machine learning frameworks including TensorFlow, PyTorch, or similar platforms * Support implementation and maintenance of cloud-based systems and services * Assist with migration of applications and infrastructure from on-premises environments to cloud platforms * Automate AI, data, and cloud-related workflows.Support security compliance initiatives across AI and cloud environments * Monitor model performance, system health, and cloud service reliability * Support troubleshooting, testing, quality assurance, and technical documentation efforts.