Senior AI Engineer

IntelliGenesis•Annapolis Junction, MD

About The Position

IntelliGenesis is seeking a Senior AI Engineer to lead the design, development, and deployment of production-grade AI systems supporting mission-critical cyber and intelligence operations. This role focuses on transitioning AI/ML capabilities from concept to operational environments, including classified and resource-constrained settings. A day in the life includes architecting scalable AI pipelines, deploying models to edge and cloud environments, integrating AI into cybersecurity workflows, and mentoring junior engineers. You will work closely with cyber operators, software engineers, and infrastructure teams to deliver impactful, real-world AI capabilities—not just research prototypes. The team dynamic is highly collaborative and mission-driven, consisting of AI engineers, cyber SMEs, and platform engineers working in agile sprints. This role serves as a technical leader and mentor, guiding best practices in MLOps, DevSecOps, and secure AI deployment.

Requirements

Must be a U.S. Citizen
Active TS/SCI Clearance and Polygraph required
10+ years of experience in AI/ML engineering, software engineering, or related field
Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred)
Strong experience deploying AI/ML models into production environment
Expertise in Python and at least one additional language (e.g., C++, Go)
Experience with MLOps tools (e.g., Kubernetes, Docker, MLflow, Kubeflow)
Experience with cloud and hybrid infrastructure (AWS, Azure, or DoD cloud environments)
Knowledge of DevSecOps and infrastructure-as-code (e.g., Terraform, Ansible)
Experience with model serving, monitoring, and lifecycle management
Familiarity with cybersecurity concepts and secure system design
Experience working in classified or regulated environments (DoD/IC preferred)

Nice To Haves

Experience with adversarial machine learning and AI security
Background in cyber operations or network traffic analysis
Experience deploying models in edge or disconnected environments
Familiarity with large language models (LLMs) and generative AI systems
Knowledge of secure enclaves and confidential computing
Prior experience supporting DoD or Intelligence Community missions
Relevant certifications (e.g., AWS Certified Solutions Architect, Security+, CISSP)

Responsibilities

Lead end-to-end AI system design, development, and deployment
Architect and implement scalable MLOps pipelines for training, validation, and deployment
Deploy AI/ML models to cloud, on-prem, and edge environments
Integrate AI capabilities into operational tools and workflows
Ensure system security, including adversarial robustness and secure model deployment
Collaborate with cross-functional teams (cyber, infrastructure, software engineering)
Mentor mid-level engineers and provide technical oversight
Rapidly prototype AI solutions and transition them into production systems
Ensure compliance with DoD Risk Management Framework (RMF) requirements