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Sr. Artificial Intelligence Engineer (5361) (TS​/SCI) (Ft. Belvoir, VA – Nolan Bldg

Job in Fort Belvoir, Fairfax County, Virginia, 22060, USA
Listing for: SMX
Full Time position
Listed on 2026-08-22
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 165000 - 180000 USD Yearly USD 165000.00 180000.00 YEAR
Job Description & How to Apply Below
Position: Sr. Artificial Intelligence Engineer (5361) (TS/SCI) (Ft. Belvoir, VA – Nolan Bldg)

SMX is seeking a Sr. Artificial Intelligence Engineer.

This is a full-time onsite position in Ft. Belvoir, VA.

Essential Duties & Responsibilities

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
Required Skills, Experience & Education
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)
Education and Experience
  • 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 (Tensor Flow, 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…
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