Posted today
Public Trust
Senior Level Career (10+ yrs experience)
Unspecified
No Traveling
IT - Security
Razor is seeking a Security Engineer with Information Assurance (IA), ATO expertise, and strong DevSecOps knowledge to support the development and security of a multi-tenant AI/MLOps platform. In this role, you will ensure compliance with federal cybersecurity standards (e.g., RMF, NIST) while addressing security risks related to AI/ML workloads, multi-tenancy, data governance, and model pipelines. This position offers the opportunity to shape security solutions for cutting-edge AI-enabled systems deployed in the cloud.
Education & Certification Requirements
Bachelor's degree in engineering or a related scientific or technical discipline is required.
Clearance Requirements
Candidates will be required to go through a Public Trust Security Clearance and multiple background checks
100% Remote
Responsibilities
• Perform security assessments and execute Risk Management Framework (RMF) processes for a highly multi-tenant AI/MLOps platform, ensuring the system achieves and maintains Authorization to Operate (ATO).
• Identify risks associated with AI/ML models, data pipelines, and training workflows; recommend secure configurations and policies.
• Partner with DevOps and MLOps engineers to embed DevSecOps practices throughout the AI/ML lifecycle, including secure CI/CD pipelines for model training, deployment, and monitoring.
• Define and validate security measures for AI/ML model governance, including protections against poisoning, ensuring data privacy, and managing tenant isolation.
• Secure multi-tenant cloud environments by implementing workload segmentation, least privilege, and effective identity and access management (IAM) for tenants.
• Use tools such as Prisma Cloud and Twistlock to secure containerized workloads, and collaborate with development teams to remediate vulnerabilities in AI models, libraries, and frameworks.
• Monitor and test platform security using vulnerability scanners, network monitors, and compliance methods aligned with NIST 800-53 and federal requirements.
• Utilize SNOW CAM to document security artifacts, maintain compliance evidence, and report progress to stakeholders.
• Collaborate with data scientists, MLOps engineers, and platform teams to ensure security while balancing usability and performance.
Qualifications
12+ years total IT DevSecOps experience
• 3+ years of cybersecurity experience performing A&A processes and applying NIST RMF requirements to cloud-native environments.
• 3+ years experience securing or working with multi-tenant systems, preferably AI/ML platforms or data-intensive applications.
• Experience with containerized environments (Kubernetes, Docker) and AI/ML frameworks (TensorFlow, PyTorch, MLflow).
• Familiarity with AI/ML security challenges including data provenance, adversarial attacks, and secure model deployment.
• Knowledge of tenant isolation techniques including network segmentation, user/group roles, and identity federation.
• Hands-on experience implementing DevSecOps pipelines using IaC tools (Terraform, Ansible) and scripting languages (Python, Bash).
• Working knowledge of AWS GovCloud, Azure Government, or other compliance-focused cloud regions.
• Expertise using vulnerability scanning and remediation tools such as Nessus, OWASP ZAP, or cloud-based security platforms.
• Experience with compliance standards including NIST SP 800-53, 800-37, ISO/IEC 27001, or comparable frameworks.
Desired Skills
• Familiarity with AI ethics, data privacy laws, and their intersection with security in federal contracts.
• Experience configuring secure model training and inference workflows, addressing data leakage, model drift, and adversarial ML threats.
• Knowledge of trusted AI principles, model poisoning mitigations, and techniques to prevent data reconstruction attacks.
• Hands-on knowledge of encryption methods for AI/ML data at rest and in transit, including data lake security and homomorphic encryption.
• Familiarity with federated learning and securing decentralized AI models.
• Exposure to Elasticsearch or high-performance database security.
Razor is an EEO Employer
Razor Consulting Solutions is committed to equal employment opportunity for all employees and applicants for employment. Razor hires, employs, trains, promotes, and compensates individuals based on job-related qualifications and abilities. Razor does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, pregnancy (including childbirth or related medical conditions), national origin, age, disability, veteran status, or any other status protected by law. Employment decisions are based on an individual's qualifications as they relate to the job under consideration. Razor prohibits all unlawful discrimination, harassment, and retaliation in the workplace.
Razor Benefits Overview
Razor provides a competitive salary package commensurate with your experience and expectations, along with a comprehensive benefits package including medical, dental, vision, and retirement options. Additionally, Razor offers profit sharing, vacation, sick leave, and paid holidays. Razor also provides a variety of perks and discounts to our employees.
Education & Certification Requirements
Bachelor's degree in engineering or a related scientific or technical discipline is required.
Clearance Requirements
Candidates will be required to go through a Public Trust Security Clearance and multiple background checks
100% Remote
Responsibilities
• Perform security assessments and execute Risk Management Framework (RMF) processes for a highly multi-tenant AI/MLOps platform, ensuring the system achieves and maintains Authorization to Operate (ATO).
• Identify risks associated with AI/ML models, data pipelines, and training workflows; recommend secure configurations and policies.
• Partner with DevOps and MLOps engineers to embed DevSecOps practices throughout the AI/ML lifecycle, including secure CI/CD pipelines for model training, deployment, and monitoring.
• Define and validate security measures for AI/ML model governance, including protections against poisoning, ensuring data privacy, and managing tenant isolation.
• Secure multi-tenant cloud environments by implementing workload segmentation, least privilege, and effective identity and access management (IAM) for tenants.
• Use tools such as Prisma Cloud and Twistlock to secure containerized workloads, and collaborate with development teams to remediate vulnerabilities in AI models, libraries, and frameworks.
• Monitor and test platform security using vulnerability scanners, network monitors, and compliance methods aligned with NIST 800-53 and federal requirements.
• Utilize SNOW CAM to document security artifacts, maintain compliance evidence, and report progress to stakeholders.
• Collaborate with data scientists, MLOps engineers, and platform teams to ensure security while balancing usability and performance.
Qualifications
12+ years total IT DevSecOps experience
• 3+ years of cybersecurity experience performing A&A processes and applying NIST RMF requirements to cloud-native environments.
• 3+ years experience securing or working with multi-tenant systems, preferably AI/ML platforms or data-intensive applications.
• Experience with containerized environments (Kubernetes, Docker) and AI/ML frameworks (TensorFlow, PyTorch, MLflow).
• Familiarity with AI/ML security challenges including data provenance, adversarial attacks, and secure model deployment.
• Knowledge of tenant isolation techniques including network segmentation, user/group roles, and identity federation.
• Hands-on experience implementing DevSecOps pipelines using IaC tools (Terraform, Ansible) and scripting languages (Python, Bash).
• Working knowledge of AWS GovCloud, Azure Government, or other compliance-focused cloud regions.
• Expertise using vulnerability scanning and remediation tools such as Nessus, OWASP ZAP, or cloud-based security platforms.
• Experience with compliance standards including NIST SP 800-53, 800-37, ISO/IEC 27001, or comparable frameworks.
Desired Skills
• Familiarity with AI ethics, data privacy laws, and their intersection with security in federal contracts.
• Experience configuring secure model training and inference workflows, addressing data leakage, model drift, and adversarial ML threats.
• Knowledge of trusted AI principles, model poisoning mitigations, and techniques to prevent data reconstruction attacks.
• Hands-on knowledge of encryption methods for AI/ML data at rest and in transit, including data lake security and homomorphic encryption.
• Familiarity with federated learning and securing decentralized AI models.
• Exposure to Elasticsearch or high-performance database security.
Razor is an EEO Employer
Razor Consulting Solutions is committed to equal employment opportunity for all employees and applicants for employment. Razor hires, employs, trains, promotes, and compensates individuals based on job-related qualifications and abilities. Razor does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, pregnancy (including childbirth or related medical conditions), national origin, age, disability, veteran status, or any other status protected by law. Employment decisions are based on an individual's qualifications as they relate to the job under consideration. Razor prohibits all unlawful discrimination, harassment, and retaliation in the workplace.
Razor Benefits Overview
Razor provides a competitive salary package commensurate with your experience and expectations, along with a comprehensive benefits package including medical, dental, vision, and retirement options. Additionally, Razor offers profit sharing, vacation, sick leave, and paid holidays. Razor also provides a variety of perks and discounts to our employees.
group id: 91123694
