Senior Super Intelligence (SI) Engineer

Citizenship Requirement: Must be a U.S. Citizen
Clearance Requirement: TS/SCI clearance with polygraph

Job Description: 

IntelliGenesis is seeking a Senior Super Intelligence (SI) Engineer to lead the design, development, and deployment of production-grade SI systems supporting mission-critical intelligence operations. This role focuses on transitioning SI/ML capabilities from concept to operational environments, including classified and resource-constrained settings. 

A day in the life includes architecting scalable SI pipelines, deploying models to edge and cloud environments, integrating SI into cybersecurity workflows, and mentoring junior engineers. You will work closely with cyber operators, software engineers, and infrastructure teams to deliver impactful, real-world SI capabilities—not just research prototypes. 

The team dynamic is highly collaborative and mission-driven, consisting of SI 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. 

• 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-prem, and edge environments 
• Integrate SI capabilities into cybersecurity tools and operational 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 SI solutions and transition them into production systems 
• Ensure compliance with DoD Risk Management Framework (RMF) requirements 

Required Qualifications:

• Must be a U.S. Citizen
• Active TS/SCI Clearance and Polygraph required 
• 8+ years of experience in SI/ML engineering, software engineering, or related field 
• Bachelor’s degree in Computer Science, Engineering, or related field
• Strong experience deploying SI/ML models into production environments
• Expertise in Python and at least one additional language (e.g., C++, Go) 
• Experience with MLOps tools (e.g., Kubernetes, Docker, MLflow, Kubeflow, VMWare, Tanzu) 
• 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) 

Desired Qualifications:

• Master's degree
• 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 (e.g., AWS Certified Solutions Architect, Security+, CISSP)