> Markdown version of [/jobs/ext/1881774-sr-artificial-intelligence-engineer-5361-ts-sci-ft-belvoi](https://www.wearedevelopers.com/jobs/ext/1881774-sr-artificial-intelligence-engineer-5361-ts-sci-ft-belvoi). 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). --- # Sr. Artificial Intelligence Engineer (5361) (TS/SCI) (Ft. Belvoi - **Company:** Smartronix, LLC - **Location:** Fort Belvoir, VA, United States - **Experience:** Expert - **Salary:** $165,000.0 - $180,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Software as a Service, Cloud Computing, Information Systems, Computer Engineering, Continuous Integration, Statistical Hypothesis Testing, Infrastructure as a Service (IaaS), Machine Learning, Open Source Technology, Platform as a Service (PAAS), Tensorflow, Secure Coding, Software Engineering, Google Cloud, Pytorch, Large Language Models, Scikit Learn, Kubernetes, Information Technology, HuggingFace, Machine Learning Operations, GPT, Docker - **Published:** August 2, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9064948/sr-artificial-intelligence-engineer-5361-tssci-ft-belvoi ## About the Role Security * Active TS security clearance and eligible for SCI and NATO read-on prior to starting work * Meet all requirements to receive a privileged user account on a TS/SCI information system (e.g. Army Cloud Computing Service Provider) prior to starting work. The requirements are currently defined in DoDD 8140.01. * Security+ or related DoDD 8140-relevant certification (or ability to obtain within 6 months of hire), * Master's degree in Computer Science, Data Science, Software Engineering, Mathematics or Statistics, Computer Engineering, Information Technology or related field and 3+ years of experience in AI/ML engineering, with demonstrable expertise in model deployment and operationalization, or * Bachelor's degree in Computer Science, Data Science, Software Engineering, Mathematics or Statistics, Computer Engineering, Information Technology or related field and 5+ years of experience in AI/ML engineering, with demonstrable expertise in model deployment and operationalization * Hands-on experience with MLOps processes, CI/CD for ML, and containerized deployment environments (Docker, Kubernetes) * Knowledge of Responsible AI frameworks and bias mitigation techniques Technical Skills * Strong proficiency in machine learning theory, model development, and deployment * Experience integrating AI solutions with LLMs (e.g., OpenAI GPT, Azure OpenAI, AWS Bedrock, or open-source alternatives) * Proficiency in Python scripting and ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face) * Knowledge of cloud platforms (AWS, Azure, GCP) and AI/ML service models (SaaS, IaaS, PaaS) * Understanding of AI security risks, threats, and vulnerabilities, and mitigation strategies * Familiarity with testing, evaluation, validation, and verification (T&E V&V) for AI systems Analytical & Communication Skills * Ability to evaluate ML model effectiveness using appropriate metrics * Skill in identifying and mitigating risks across the AI lifecycle * Strong technical writing and presentation skills * Ability to tailor technical information to diverse audiences Professional Attributes: * Judgment - Assessing trade-offs and making informed technical decisions * Problem-solving - Framing complex challenges and developing actionable solutions * Execution orientation - Delivering results in dynamic, fast-paced environments * Innovation & creativity - Recommending improvements and exploring emerging AI capabilities * Risk-centered mindset - Understanding threats, vulnerabilities, and mission impacts * Trustworthiness - Operating with integrity in highly sensitive environments Desired Skills/Experience * Experience with DoD AI Ethical Principles (responsible, equitable, traceable, reliable, governable) * Familiarity with NIST Risk Management Framework (RMF) or cybersecurity compliance standards * Experience in defense or IC AI/ML projects * Relevant certifications (e.g., AWS Certified Machine Learning, Azure AI Engineer, TensorFlow Developer) ## Description AI Model Lifecycle & MLOps * Design, develop, and deploy machine learning models to achieve organizational mission objectives * Implement MLOps processes and CI/CD pipelines in containerized or reproducible computing environments to support the full ML lifecycle * Assess and address limitations of methods to deliver machine learning models in production * Conduct AI risk assessments to ensure models and solutions are performing as designed * Monitor, evaluate, and optimize ML model performance using appropriate metrics LLM Integration & Application Development * Integrate AI solutions with cloud and enterprise IT infrastructure * Design and implement AI-enabled applications leveraging Large Language Models (LLMs) and foundation models * Automate development, testing, security, and deployment of AI/ML-enabled software * Develop APIs and interfaces to enable secure, scalable interaction with AI models * Implement Responsible AI best practices aligned with DoD AI Ethical Principles Technical Leadership & Collaboration * Mentor and provide technical guidance to junior AI/ML engineers and data scientists. * Serve as the technical lead for AI solution architecture, making final determinations on model selection and deployment frameworks. * Analyze ML model outputs and translate results for technical and non-technical stakeholders * Explain AI concepts and terminology clearly to cross-functional teams * Identify low-probability, high-impact risks in ML training data and throughout the AI solution lifespan * Research and evaluate the latest ML and AI tools, techniques, and best practices * Write and document reproducible, secure code with proper error handling Mission Support * Collaborate with stakeholders to address data privacy, PII, PHI, and data reusability concerns * Ensure AI design and development activities are properly documented and updated * Conduct hypothesis testing using statistical processes * Use knowledge of business processes to create or recommend AI solutions ## Related Videos - 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Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Building Sovereign AI: Lessons from Deploying Secure RAG Systems using Confidential Computing](https://www.wearedevelopers.com/videos/100108-building-sovereign-ai-lessons-from-deploying-secure-rag-systems-using-confidential-computing) - [Speak, Code, Deploy: Transforming Developer Experience with Voice Commands](https://www.wearedevelopers.com/videos/1159-speak-code-deploy-transforming-developer-experience-with-voice-commands) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) ## 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) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Got AI ideas but no money? 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