Sr. Staff AI Security Architect
$95 - $110 per hourMondo Staffing
Job Title: Sr. Staff AI Security Architect
Location-Type: Remote
Duration: Contract-to-Hire
Compensation Range: $95-110/hour
Benefits: Eligible for Health, Dental, Vision, and 401K
Visa Sponsorship: Not eligible for visa sponsorship
Job Description:
This role defines and advances the enterprise security architecture for AI, generative AI, and agentic AI, enabling the client to adopt AI technologies securely and responsibly across a regulated environment.
Job Summary
•Define and maintain security-by-design standards and governance controls across the AI model lifecycle, including generative AI and agentic AI systems.
•Lead AI threat modeling and control design, serving as the enterprise authority on AI security risk across cross-functional initiatives.
•Partner with Security, Architecture, Data, Product, Legal, Risk, and Compliance teams to embed security requirements into AI development and deployment workflows.
•Bridge communication between executive leadership, development groups, and security teams to align on AI risk posture and control strategies.
•Evaluate AI risk using established frameworks and translate findings into actionable remediation guidance for engineering and product teams.
•Govern DevSecOps and MLOps security practices, including CI/CD control integration, container security, and security telemetry pipelines.
•Serve as a thought leader and cultural driver for responsible AI adoption, influencing senior stakeholders and shaping organizational security maturity.
Minimum Requirements:
•10 years of experience in security architecture spanning cloud, platform, or application security domains.
•5 years designing enterprise security architectures in regulated industries such as financial services, insurance, or healthcare.
•2-3 years of hands-on experience with AI/ML systems, including LLMs, agentic architectures, orchestration layers, and common generative AI patterns such as RAG and vector databases.
•Demonstrated expertise in AI risk assessment frameworks, including NIST AI RMF and OWASP Top 10 for LLMs.
•Expertise in cloud and Zero Trust security, including IAM, API security, and service-to-service authentication, with experience on AWS or Azure.
•Strong application security background covering secure coding, threat modeling, and OWASP Top 10 remediation guidance.
•Proven ability to influence senior and executive stakeholders and lead security architecture across complex, cross-functional programs.
Preferred Qualifications:
•Bachelor's or master's degree in Computer Science, Engineering, or a related field.
•Advanced security architecture certifications such as CISSP-ISSAP or GIAC credentials.
•Hands-on LLMOps security experience, including model registry governance, artifact signing, evaluation pipelines, and drift monitoring.
•Experience leading AI security assessments and red- or purple-team exercises against production AI systems.
•Familiarity with infrastructure- and policy-as-code practices and automated security gates within CI/CD pipelines.
•AI governance and risk program experience, including model inventory management, risk tiering, control mapping, and audit evidence preparation.
•Generative AI data protection experience covering DLP, sensitive-data detection, masking, tokenization, and content governance.
Location-Type: Remote
Duration: Contract-to-Hire
Compensation Range: $95-110/hour
Benefits: Eligible for Health, Dental, Vision, and 401K
Visa Sponsorship: Not eligible for visa sponsorship
Job Description:
This role defines and advances the enterprise security architecture for AI, generative AI, and agentic AI, enabling the client to adopt AI technologies securely and responsibly across a regulated environment.
Job Summary
•Define and maintain security-by-design standards and governance controls across the AI model lifecycle, including generative AI and agentic AI systems.
•Lead AI threat modeling and control design, serving as the enterprise authority on AI security risk across cross-functional initiatives.
•Partner with Security, Architecture, Data, Product, Legal, Risk, and Compliance teams to embed security requirements into AI development and deployment workflows.
•Bridge communication between executive leadership, development groups, and security teams to align on AI risk posture and control strategies.
•Evaluate AI risk using established frameworks and translate findings into actionable remediation guidance for engineering and product teams.
•Govern DevSecOps and MLOps security practices, including CI/CD control integration, container security, and security telemetry pipelines.
•Serve as a thought leader and cultural driver for responsible AI adoption, influencing senior stakeholders and shaping organizational security maturity.
Minimum Requirements:
•10 years of experience in security architecture spanning cloud, platform, or application security domains.
•5 years designing enterprise security architectures in regulated industries such as financial services, insurance, or healthcare.
•2-3 years of hands-on experience with AI/ML systems, including LLMs, agentic architectures, orchestration layers, and common generative AI patterns such as RAG and vector databases.
•Demonstrated expertise in AI risk assessment frameworks, including NIST AI RMF and OWASP Top 10 for LLMs.
•Expertise in cloud and Zero Trust security, including IAM, API security, and service-to-service authentication, with experience on AWS or Azure.
•Strong application security background covering secure coding, threat modeling, and OWASP Top 10 remediation guidance.
•Proven ability to influence senior and executive stakeholders and lead security architecture across complex, cross-functional programs.
Preferred Qualifications:
•Bachelor's or master's degree in Computer Science, Engineering, or a related field.
•Advanced security architecture certifications such as CISSP-ISSAP or GIAC credentials.
•Hands-on LLMOps security experience, including model registry governance, artifact signing, evaluation pipelines, and drift monitoring.
•Experience leading AI security assessments and red- or purple-team exercises against production AI systems.
•Familiarity with infrastructure- and policy-as-code practices and automated security gates within CI/CD pipelines.
•AI governance and risk program experience, including model inventory management, risk tiering, control mapping, and audit evidence preparation.
•Generative AI data protection experience covering DLP, sensitive-data detection, masking, tokenization, and content governance.
Vacancy posted 3 days ago
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