> Markdown version of [/jobs/ext/3461613-ai-engineer-ii](https://www.wearedevelopers.com/jobs/ext/3461613-ai-engineer-ii). 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). --- # AI Engineer II - **Company:** Kansas City National Security Campus - **Location:** Kansas City, MO, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, Big Data, Business Software, Continuous Delivery, Continuous Integration, Distributed Computing Environment, Machine Learning, Natural Language Processing, Software Engineering, Systems Architecture, User-Centered Design, Large Language Models, Apache Spark, Generative AI, Backend, Git, Integration Tests, Information Technology, Low Latency, Apache Kafka, Front End Software Development, Api Design, Software Version Control, Microservices - **Published:** September 20, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=1b0cffe0be58622b ## About the Role * Bachelors degree in quantitative field * At least two years relevant experience in computer science, data science, or related technical activities * Ability to travel as determined by the needs of the business * Ability to work on-site as directed by management and as determined by the needs of the business * Regular and reliable attendance is an essential function of this job * United States Citizenship * Ability to obtain and maintain, if required for position, a U.S. Department of Energy (DOE) security clearance (some positions require additional DOE designations), * Ability to grasp complex technical and business problems, prioritize tasks, and devise innovative, production ready AI solutions that align with manufacturing or enterprise objectives. * Demonstrated software engineering discipline: version control, unit/integration testing, continuous integration-continuous deployment (CI/CD), and documentation of code and system architecture. * Strong communication skills (verbal, written, presentation) to convey technical concepts to stakeholders, collaborate with cross-functional teams, and produce clear technical specifications and run books. * Deep knowledge of machine learning and deep learning concepts, including model design, training, evaluation, and optimization for performance, latency, and resource utilization. * Familiarity with distributed data processing frameworks and big data ecosystems (e.g., Spark, Kafka) to support high throughput training and real time inference pipelines. * Proven ability to create actionable visualizations or dashboards that surface model performance, data quality, and operational metrics for end users and decision makers. * Experience with API development, microservices architecture, and version control systems (Git). * Hands-on experience deploying AI applications on cloud platforms such as Azure or AWS. * Solid understanding of Large Language Models (LLMs), Natural Language Processing (NLP), and Retrieval-Augmented Generation (RAG)., We are required by the Department of Energy (DOE) to conduct a pre-employment drug test and background review, including checks of references, credit, law enforcement records and employment/education history. Applicants must be able to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship. Dual citizenship may affect clearance eligibility., If you have a medical portable electronic device (MedPED) - such as a pacemaker, defibrillator, drug-releasing pump, hearing aids or diagnostic equipment used to measure or monitor body functions - you may be required to meet NNSA security requirements if employed by us. ## Description Contributes to the end-to-end design, development, productionization, and ongoing support of advanced artificial intelligence solutions for manufacturing or business applications, ensuring models are scalable, reliable, and seamlessly integrated into frontend and backend systems., * Develop AI/ML models and algorithms using disciplined software-engineering practices, including version control, automated testing, and thorough documentation. * Contribute to designing, building, and maintaining production-grade pipelines for model training, validation, deployment, and monitoring, applying CI/CD and modern orchestration and deployment practices. * Optimize model performance for latency, throughput, and resource utilization to meet real-time manufacturing or business requirements. * Collaborate with multiple stakeholders to translate business needs into AI system specifications, define service-level objectives, and provide technical guidance to data science partners.