Senior AI Engineer with Security Clearance

IntelliGenesis LLC®; Herndon (VA); On-site; USD 150,000 - 230,000; Full time

Job summary

IntelliGenesis LLC seeks a Senior AI Engineer to lead the design, development, and deployment of production-grade AI systems for mission-critical intelligence operations. This role focuses on transitioning AI/ML from concept to operational environments, including edge and cloud deployments, with DoD RMF compliance.

You will architect scalable AI pipelines, deploy models to edge and cloud environments, integrate AI into cybersecurity workflows, and mentor junior engineers in a collaborative,

Qualifications

• U.S. citizen with active TS/SCI clearance and polygraph.
• 8+ years' AI/ML or software engineering experience.
• Bachelor's degree in CS, engineering, or related field.
• Production deployment of AI/ML models required.
• Strong Python and at least one other language (C++, Go).
• Experience with MLOps tools: Kubernetes, Docker, MLflow, Kubeflow.
• Cloud/hybrid infra experience: AWS, Azure, or DoD cloud.
• Knowledge of DevSecOps and IaC (Terraform, Ansible).
• Familiar with secure design, RMF, and regulated environments.

Responsibilities

• Lead end-to-end AI system design, development, and deployment.
• Architect scalable MLOps pipelines for training, validation, deployment.
• Deploy AI/ML models to cloud, on-prem, and edge environments.
• Integrate AI capabilities into cybersecurity tools and workflows.
• Mentor mid-level engineers and provide technical oversight.
• Ensure secure model deployment and RMF compliance.

Skills

Python

ML engineering

C++

Go

MLOps

Cloud & edge computing

Education

Bachelor's degree in Computer Science or related field

Tools

Kubernetes

Docker

MLflow

Kubeflow

Terraform

Ansible

VMware Tanzu

Job description

Citizenship Requirement: Must be a U.S. Citizen

Clearance Requirement: TS/SCI clearance with polygraph

Job Description: IntelliGenesis is seeking a Senior AI Engineer to lead the design, development, and deployment of production-grade AI systems supporting mission-critical 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.

* 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 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 AI 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 AI/ML engineering, software engineering, or related field
• Bachelor's degree in Computer Science, Engineering, or related field
• Strong experience deploying AI/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 managementFamiliarity 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 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)