Senior AI Engineer

About the role

The Senior AI Engineer will lead the design, development, and deployment of production-grade AI systems supporting mission-critical cyber and intelligence operations. This role involves transitioning AI/ML capabilities from concept to operational environments, including classified and resource-constrained settings.

Responsibilities

• Have a direct impact on national security and cyber operations
• Work on cutting-edge AI systems in fast-paced environments
• Opportunity to lead architecture and influence technical direction
• Hands-on role across the full AI lifecycle (design → deploy → scale)
• Strong alignment with DoD modernization and AI initiatives
• 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

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)
• 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)

Qualifications

• 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)
• 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)

Skills

• 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)
• 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)

Benefits

IntelliGenesis is committed to providing equal opportunity to all employees and applicants for employment. The Company is an Equal Opportunity Employer (EOE), and as such, does not tolerate discrimination, retaliation, or harassment of its employees or applicants based upon race, color, religion, gender, sexual orientation, national origin, age, genetic information, disability, or any other protected characteristic under local, state, or federal law in any employment practice. Such employment practices include, but are not limited to: hiring, promotion, demotion, transfer, recruitment, or recruitment advertising, selection, disciplinary action, layoff, termination, rates of pay, or other forms of compensation and selection of training.

Pay

Compensation ranges encompass a total compensation package and are a general guideline only and not intended as a guaranteed and/or implied final compensation or salary for this job opening. Determination of official compensation or salary relies on several different factors including, but not limited to: level of position, complexity of job responsibilities, geographic location, candidate’s scope of relevant work experience, educational background, certifications, contract-specific affordability, organizational requirements and alignment with local market data.

Schedule

Details about the schedule are not specified in the job posting.