AI Security Engineer – Mid

Jobtailor; Washington (Washington County); On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor is seeking an experienced AI Security Engineer to design, train and operate ML models for threat detection and compliance monitoring. You will integrate AI with security tools and collaborate with SOC and security engineering teams to implement SIEM enhancements and automated incident response.

Ideal candidates have 4+ years in IT/cybersecurity, hands‑on ML for security, and strong knowledge of FISMA/NIST guidelines.

Qualifications

• Bachelor’s degree in CS/AI/Cybersecurity or related field from an accredited university.
• Minimum of 4 years in information technology or cybersecurity.
• At least 2 years hands‑on AI security engineering or ML development in a complex enterprise.
• Experience developing, training and deploying ML models for security or data analytics.
• Experience integrating AI/ML into enterprise security tools and workflows.
• Familiarity with FISMA, NIST SP 800-53 and AI governance guidelines.
• Ability to obtain MBI or higher, PIV credentials and IT access authorities.
• Top Secret clearance access if required during performance period.
• Strong English communication, both written and oral.
• Hands‑on expertise in supervised and unsupervised learning, NN, NLP, anomaly detection, predictive analytics.
• Proficiency with TensorFlow, PyTorch, scikit‑learn; Python, PowerShell, SQL, JSON.
• Experience with AI‑driven SIEM (Microsoft Sentinel) and CI/CD in DevSecOps.
• Familiarity with AI governance and NIST RMF; knowledge of FedRAMP and NIST SP 800‑207.
• Familiarity with SOC operations, incident response, threat intel, vulnerability mgmt, security eng.
• Experience documenting AI systems and privacy/compliance considerations.
• Experience assessing supply chain risks of third‑party AI tools in federal IT.

Responsibilities

• Support design, development, testing, deployment, and maintenance of AI security solutions for threat detection and response.
• Develop and maintain ML models for anomaly detection, threat analytics, and automated threat hunting.
• Implement AI‑driven SIEM enhancements (Microsoft Sentinel or equivalent) including detection rules and UEBA.
• Integrate AI with SIEM/EDR/threat intel/vulnerability mgmt and SOC workflows.
• Automate incident response, vulnerability prioritization, and compliance assessment using AI and scripting.
• Develop automated compliance tools for NIST SP 800‑53, FISMA, and agency standards.
• Implement AI‑driven risk assessment methodologies, data pipelines, scoring, and visualization.
• Support fraud detection, policy enforcement, risk mitigation and regulatory reporting with AI.
• Collaborate with AI Security Engineer Lead, SOC tech lead, cybersecurity architect, and teams.
• Document model development, architectures, training parameters, evaluation metrics, and deployment configs.
• Maintain CI/CD pipelines for AI model updates and performance monitoring.
• Monitor model drift, accuracy, false positives/negatives, and adversarial risks.

Skills

AI Security Engineering

Machine Learning Development

Microsoft Sentinel

FISMA Compliance

CI/CD Pipeline Management

Anomaly Detection

NIST RMF

Communication Skills

Supervised Learning

Unsupervised Learning

Natural Language Processing

Predictive Analytics

Education

Bachelor’s degree in Computer Science / Artificial Intelligence / Cybersecurity / Information Systems / Data Science

Tools

TensorFlow

PyTorch

scikit-learn

Python

PowerShell

SQL

JSON

Job description

• Support the design, development, testing, deployment, and maintenance of AI-powered security solutions for threat detection, automated incident response, behavioral analytics, and compliance monitoring
• Develop and maintain machine learning models for anomaly detection, predictive threat analytics, and automated threat hunting
• Implement and maintain AI-driven SIEM enhancements in Microsoft Sentinel or equivalent platforms, including detection rules, UEBA configurations, and automated response playbooks
• Integrate AI capabilities with SIEM, EDR, threat intelligence, vulnerability management, and SOC workflows
• Automate incident response, vulnerability prioritization, compliance assessment, and risk management workflows using AI and scripting
• Develop automated compliance monitoring tools for NIST SP 800-53, FISMA, and agency-specific standards
• Implement AI-driven risk assessment methodologies, data pipelines, scoring models, and visualization capabilities
• Support fraud detection, policy enforcement, risk mitigation, and regulatory reporting using AI
• Support secure integration and governance of Perplexity and related AI tools
• Develop, train, evaluate, and operationalize machine learning models
• Implement and maintain CI/CD pipelines for AI model updates and performance monitoring
• Monitor model drift, accuracy degradation, false positive/negative changes, and adversarial manipulation risks
• Optimize model computational efficiency, resource utilization, and detection accuracy
• Test and validate AI model outputs with SOC analysts and security engineers
• Document model development, architectures, training parameters, evaluation metrics, and deployment configurations
• Support AI governance, risk assessments, privacy and compliance reviews, model inventories, and AI lifecycle management
• Integrate AI risk management into enterprise RMF and FISMA programs
• Support AI supply chain risk assessments
• Collaborate with the AI Security Engineer Lead, SOC technical lead, cybersecurity architect, security engineering teams, and functional leads
• Participate in technical working sessions, architecture reviews, and sprint planning
• Maintain system descriptions, architecture diagrams, data flow diagrams, model documentation, runbooks, and SOPs
• Prepare program deliverables, status reports, recommendations, plans, reviews, and assessment reports
• Provide technical support to ISSO and SCA personnel for AI system FISMA documentation and assessment evidence
• Support AI security awareness briefings and training materials

Requirements

• Bachelor’s degree in computer science, Artificial Intelligence, Cybersecurity, Information Systems, Data Science, or a related field from an accredited college or university
• Minimum of 4 years of experience in information technology or cybersecurity
• At least 2 years of demonstrated hands‑on experience in AI security engineering, machine learning development, or AI governance within a complex enterprise IT environment
• Demonstrated experience developing, training, and deploying machine learning models for security or data analytics applications
• Experience integrating AI or machine learning capabilities into enterprise security tools or operational workflows
• Familiarity with FISMA, NIST SP 800-53, and applicable AI governance guidelines
• Ability to obtain and maintain a Minimum Background Investigation (MBI) or higher, PIV credentials, and requisite IT access authorizations
• Must be eligible for Top Secret clearance access if required during the period of performance
• Strong communication skills in English, written and oral
• Hands‑on expertise in supervised and unsupervised learning, neural networks, natural language processing, anomaly detection algorithms, and predictive analytics
• Proficiency with TensorFlow, PyTorch, scikit-learn, or equivalent
• Proficiency with Python, PowerShell, SQL, and JSON
• Experience with AI-driven SIEM capabilities, including Microsoft Sentinel or equivalent
• Experience developing and maintaining CI/CD pipelines in a DevSecOps environment
• Familiarity with AI governance principles and NIST AI RMF or equivalent federal standards
• Knowledge of FISMA, NIST SP 800-53, NIST SP 800-207, OMB M-22-09, and FedRAMP
• Familiarity with SOC operations, incident response, threat intelligence, vulnerability management, and security engineering
• Experience developing and maintaining technical documentation for AI systems and cybersecurity capabilities
• Familiarity with privacy and data protection requirements applicable to AI systems
• Experience assessing supply chain risks associated with third‑party AI tools, models, and data sources within a federal IT environment

Core Competencies

Demonstrates expertise in developing and deploying AI-powered security solutions, including machine learning models for threat detection and compliance monitoring. Proficient in integrating AI capabilities with security tools and workflows while ensuring adherence to regulatory standards such as FISMA and NIST.

Highest‑signal resume keywords

• AI Security Engineering
• Machine Learning Development
• Microsoft Sentinel
• FISMA Compliance
• CI/CD Pipeline Management

Hard Skills

• Machine Learning Models
• Anomaly Detection Algorithms
• Predictive Analytics
• Supervised Learning
• Unsupervised Learning
• Natural Language Processing
• Python
• PowerShell
• SQL
• TensorFlow

Soft Skills

• Strong Communication Skills

Certifications & Qualifications

• Top Secret Clearance Eligibility
• Minimum Background Investigation (MBI)

Industry Keywords

• NIST SP 800-53
• AI Governance
• Cybersecurity
• Risk Management Framework (RMF)
• Supply Chain Risk Assessment

Tools & Technologies

• Microsoft Sentinel
• AI-Driven SIEM
• DevSecOps
• Scikit-learn
• PyTorch