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Cyber Security AI SaaS Security ArchitectNucoreVision • Washington, Utah, United States
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Cyber Security AI SaaS Security Architect

NucoreVision
  • US
    Washington, Utah, United States
  • US
    Washington, Utah, United States
Postuler Maintenant

À propos

Cyber Security AI SaaS Security Architect
We are seeking an experienced Cyber Security AI SaaS Security Architect to lead the secure design and governance of AI environments across the enterprise. In this role, you will help shape how generative AI, AI-enabled SaaS platforms, model pipelines, and supporting data ecosystems are adopted securely, responsibly, and at scale. You will partner with security, engineering, data, product, privacy, and compliance teams to define guardrails, reduce emerging risks, and enable innovation with confidence.
About the Role This is a high-impact architecture role for a security professional who understands both modern cybersecurity practices and the evolving risks introduced by AI in a SaaS environment. You will design secure patterns for AI systems across training, deployment, inference, integrations, and monitoring, while helping the organization build practical and scalable governance for AI use. The ideal candidate is equally comfortable advising senior stakeholders, reviewing technical designs, and translating emerging AI threats into actionable controls.
Requirements
U.S. Citizenship is required
Must have or be able to receive a Public Trust
Candidate must live in the Washington, D.C., metropolitan area. The position i a hybrid roe and requires working onsite for three days and remotely two days in Washington, D.C.
Key Responsibilities
Design secure reference architectures for AI and generative AI solutions, including data ingestion, model training, fine-tuning, deployment, inference, and AI-enabled SaaS integrations.
Design and implement practical security guardrails to prevent prompt injection, data leakage, and model supply-chain risks in AI/SaaS systems.
Lead AI-focused threat modeling and risk assessments covering issues such as prompt injection, data leakage, model inversion, adversarial manipulation, model poisoning, and software supply chain risk.
Partner with engineering, data science, product, legal, privacy, and compliance teams to embed secure-by-design practices into AI workflows and release processes.
Establish policies, standards, and governance controls for acceptable AI use, data protection, model access, retention, auditability, and third-party oversight.
Support architecture reviews, security testing, adversarial validation, and control assessments for AI systems before and after deployment.
Recommend monitoring, detection, and response approaches for AI-related misuse, drift, abuse, and high-risk behavior.
Translate technical risks into clear architectural guidance and business-focused recommendations for stakeholders and leadership.
Required Qualifications
Bachelor's degree in Cybersecurity, Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.
8+ years of experience in security architecture, cloud security, application security, or enterprise risk management.
Strong understanding of AI, machine learning, and generative AI concepts, including large language models, model pipelines, and AI-enabled applications.
Hands‑on experience with core security domains such as identity and access management, encryption, data protection, secure software design, logging, monitoring, and incident response.
Experience conducting threat modeling, architecture reviews, and security control design for complex technology environments.
Knowledge of AI governance, privacy, and compliance requirements, including risk frameworks and audit expectations.
Excellent communication skills, with the ability to work effectively across technical, business, and leadership audiences.
Preferred Qualifications
Experience securing generative AI, retrieval‑augmented generation, AI agents, or enterprise AI platforms in production environments.
Familiarity with frameworks and standards such as NIST AI RMF, OWASP guidance for LLM applications, ISO 42001, SOC 2, GDPR, HIPAA, or similar requirements.
Experience with SaaS security posture management, third‑party risk reviews, and cloud‑native security controls.
Relevant certifications such as CISSP, CCSP, SABSA, cloud security certifications, or specialized AI security training.
Experience working in regulated industries or large, complex enterprise environments.
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  • Washington, Utah, United States

Compétences linguistiques

  • English
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