Senior Super Intelligence (SI) Engineer

IntelliGenesis•Annapolis Junction, MD

About The Position

IntelliGenesis is seeking a Senior Super Intelligence (SI) Engineer to lead the design, development, and deployment of production-grade SI systems supporting mission-critical cyber and intelligence operations. The role focuses on transitioning SI/ML capabilities from concept to operational environments, including classified and resource-constrained settings. The engineer will architect scalable SI pipelines, deploy models to edge and cloud environments, integrate SI into cybersecurity workflows, and mentor junior engineers. The role works closely with cyber operators, software engineers, and infrastructure teams to deliver operational capabilities rather than research prototypes. The team is collaborative and mission-driven, working in agile sprints with SI engineers, cyber SMEs, and platform engineers. The position provides technical leadership and mentorship, guiding best practices in MLOps, DevSecOps, and secure AI deployment.

Requirements

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

Nice To Haves

Master’s degree.
DoD or Intelligence Community experience.
Experience with adversarial machine learning and SI 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 SI systems.
Knowledge of secure enclaves and confidential computing.
Prior experience supporting DoD or Intelligence Community missions.
Relevant certifications such as AWS Certified Solutions Architect, Security+, or CISSP.

Responsibilities

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