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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal AI Software Engineer (AHT) - **Company:** Northrop Grumman - **Location:** Beavercreek, OH, United States - **Salary:** $125,300.0 - $187,900.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Computing Platforms, Artificial Neural Networks, Business Software, Software Debugging, Decision Support Systems, Linux, DevOps, Genetic Algorithm, Graph Database, Machine Learning, Pattern Recognition, Rapid Prototyping Process, Tensorflow, Robotic Automation Software, Signal Processing, Software Engineering, Unstructured Data, Reinforcement Learning, Data Processing, Pytorch, Flask (Web Framework), Large Language Models, Prompt Engineering, Deep Learning, Convolutional Neural Networks, Keras, Fastapi, Containerization, Scikit Learn, Kubernetes, Information Technology, Modeling and Simulation, Machine Learning Operations, Software Version Control, Devsecops, Unsupervised Learning, Microservices - **Published:** August 14, 2026 - **Apply:** https://www.careerjet.com/job/usf40ebda65d9d082a46418d77f5e45168/eaa ## About the Role * Bachelor's degree in Computer Science or a related STEM field with 5 years of relevant experience, or master's degree in Computer Science or a related STEM field with 3 years of relevant experience; an additional 4 years of relevant experience may be considered in lieu of a degree. * Experience implementing and/or applying one or more AI models and algorithms (for example: LLMs, deep neural networks, genetic algorithms, embedding models, deep learning architectures). * Experience developing systems using AI/ML frameworks and libraries such as PyTorch, TensorFlow, Keras, or Scikit-learn. * Experience across the ML pipeline, including: * Working with novel or heterogeneous datasets. * Data processing and preparation. * Training and fine-tuning ML systems. * Modifying existing deep learning architectures and implementing models from architecture diagrams. * Evaluating system performance using established and custom metrics and methods. * Ability to perform rapid prototyping and proof-of-concept implementations. * General familiarity with applied machine learning concepts, including multilayer perceptrons, convolutional neural networks (CNNs), recurrent architectures such as LSTMs, transformer models, supervised and unsupervised learning methods, reinforcement learning methods, and statistical or graphical models. * General familiarity with computational and statistical learning theory. * Experience with web application development frameworks such as Flask or FastAPI. * Understanding of software engineering practices, including use of source control and basic software architecture concepts. * Ability to obtain a U.S. Government TS/SCI security clearance with CI Poly, * Active TS/SCI clearance with CI Poly * Experience with AWS or other commercial cloud computing platforms. * Experience with microservice architectures and related practices, including containerization and container orchestration technologies. * Familiarity with explainable AI, adversarial AI, active learning, and third-wave AI approaches. * Familiarity with DevOps, DevSecOps, and/or MLOps concepts and workflows. * Familiarity with Linux-based operating systems. * Experience working independently to plan and execute technical tasks. * Hands-on experience with LLMs (e.g., prompt design/engineering, use of LLM development frameworks, fine-tuning, or model quantization). * Experience with modeling and simulation. * Experience using vector databases and/or graph databases. ## Description * Define, develop, and deliver mathematical and statistical models and algorithms to address prediction, optimization, and classification problems. * Apply machine learning algorithms to large structured and unstructured datasets for use cases such as autonomy, pattern recognition, target detection and tracking, recommendation and decision support systems, signals processing, and robotic systems. * Design, develop, document, test, debug, and deploy AI/ML applications. * Collaborate with cross-functional teams to deploy AI/ML solutions in development and production environments. * Prepare and present technical progress and results to internal and external stakeholders. ## Related Videos - [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [#90DaysOfDevOps - The DevOps Learning Journey](https://www.wearedevelopers.com/videos/548-90daysofdevops-the-devops-learning-journey) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Got AI ideas but no money? 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