Principal Cloud Security Architect
Role details
Job location
Tech stack
Job description
Are you a visionary leader ready to redefine the future of cloud security? We re looking for a Principal Cloud Security Architect to spearhead our organization s journey toward a secure, innovative, and future-proof cloud ecosystem. In this strategic role, you will collaborate seamlessly with Infrastructure, Development, and Data/AI teams to design and execute state-of-the-art security strategies that drive digital transformation, safeguard critical assets, and accelerate platform adoption. Your leadership will be instrumental in shaping resilient, scalable cloud and AI-powered solutions that empower business growth while maintaining the highest standards of security and integrity. Key Responsibilities Include:
- Defining cloud and AI security architecture patterns and standards based on industry best practices.
- Collaborating with domain architects, data scientists, and lead security engineers to design and implement security controls across cloud, data, and AI/ML systems aligned with enterprise frameworks.
- Driving security governance across multi-cloud and AI/ML platforms, ensuring secure deployment, operation, and monitoring of applications and models.
- Applying deep expertise in cloud security, AI/ML security, network architecture, system hardening, and observability to lead technical operations teams in the containment and remediation of security incidents.
- Supporting incident response efforts, including AI/ML-specific threats (model compromise, data poisoning, adversarial attacks), ensuring lessons learned are incorporated into future architecture.
- This role requires a strong combination of strategic vision, technical expertise, and cross-functional leadership to deliver scalable, secure, and compliant cloud and AI-enabled solutions across the enterprise.
Key Responsibilities:
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Cloud & AI Security Strategy & Architecture
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Lead the development of cloud and AI security architecture strategy, including frameworks, standards, guidelines, and procedures for infrastructure, software, and machine learning systems.
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Design solutions that integrate industry-standard frameworks (e.g., NIST 800-53, ISO 27002, SABSA) along with emerging AI security frameworks (e.g., NIST AI RMF, OWASP Top 10 for LLMs) into enterprise architecture.
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Define and maintain security roadmaps guiding adoption of secure cloud, data platforms, and AI/ML technologies (GenAI, LLMs, predictive models).
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Act as a senior security advisor to architecture committees, guiding secure AI adoption, model governance, and ethical AI practices.
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Partner with application, infrastructure, DevOps, and Data/AI teams to implement secure MLOps and LLMOps pipelines aligned with enterprise controls.
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Advocate for secure-by-design and responsible AI principles, including fairness, explainability, and accountability.
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Risk & Threat Management
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Lead cloud and AI security risk assessments, identifying vulnerabilities across infrastructure, data pipelines, and ML models.
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Establish and maintain an enterprise threat management program, including AI-specific threat modeling (e.g., model inversion, prompt injection, data leakage).
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Integrate AI threat intelligence and anomaly detection into SOC operations.
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Assist Security Operations in incident response, including AI/ML attack vectors, ensuring continuous improvement of detection and response mechanisms.
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Secure Development, AI/ML Security & Data Protection
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Build and maintain the Secure Software Development Lifecycle (SSDLC) and extend it to Secure ML Lifecycle (SMLC) practices.
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Define and enforce secure MLOps practices, including model validation, versioning, monitoring, and rollback mechanisms.
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Oversee secure handling of training data, feature stores, and model artifacts, ensuring protection against data leakage and poisoning.
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Implement controls for LLM usage, including prompt security, output filtering, and sensitive data protection.
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Lead enterprise data protection initiatives, including privacy-preserving AI techniques (e.g., differential privacy, anonymization, encryption).
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Technology Enablement & Vendor Management
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Evaluate and lead proof-of-concepts for cloud and AI security technologies (e.g., model security tools, AI observability platforms, LLM guardrails).
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Assess third-party AI/ML platforms and vendors for security, privacy, and compliance risks.
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Stay current with evolving cloud, cybersecurity, and AI threat landscapes to guide innovation and investment decisions.
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Mentor teams on AI security best practices, secure architecture patterns, and emerging risks., * Participate in OP monthly team meetings and participate in team-building efforts.
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Contribute to OP technical discussions, peer reviews, etc.
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Contribute content and collaborate via the OP-Wiki/Knowledge Base.
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Provide status reports to OP Account Management as requested.
Requirements
- A bachelor s degree in Computer Science, Engineering, or a related technical field is required., * 15+ years of progressive experience in Information Security and Risk Management, including:
- Minimum 5 years in Security Architecture, with deep involvement in strategic design and implementation.
- Minimum 5 years working in cloud environments (IaaS, PaaS, SaaS), across platforms such as AWS, Azure, or GCP.
- Demonstrated experience or strong exposure to AI/ML security, MLOps, or data security in AI-driven environments.
- Proven experience managing complex cloud and AI-enabled security initiatives across enterprise environments.
- Strong communication and leadership skills, with the ability to influence executive management and technical stakeholders.
Technical Expertise:
- Deep understanding of cloud-native and AI security principles, including:
- Cloud Architecture & Networking
- Identity & Access Management (IAM)
- CI/CD & MLOps/LLMOps Security
- Secrets Management & Data Protection
- Logging, Detection, and Incident Response
- Container & Kubernetes Security
- AI/ML Security Concepts, including:
- Model security (theft, tampering, inversion)
- Adversarial machine learning
- Prompt injection and LLM vulnerabilities
- Data poisoning and data lineage risks
- AI model monitoring and drift detection
Frameworks & Standards:
- CIS Benchmarks, Cloud Security Alliance (CSA)
- NIST SP standards (800-144, 800-145, etc.)
- NIST AI Risk Management Framework (AI RMF)
- OWASP Top 10 for LLM Applications
- Privacy and regulatory frameworks (GDPR, HIPAA, PCI-DSS, etc.)
Demonstrated Success In:
- Leading enterprise-scale security programs (SOC, DLP, SSDLC, IAM, AI governance)
- Architecting Zero Trust models across cloud and AI ecosystems
- Designing and implementing secure AI adoption strategies and governance frameworks
- Advising on compliance, privacy, and ethical AI practices
Additional Experience:
- Experience with SD-WAN, IoT, Wireless Networking, and AI/GenAI platforms
- Strong background in risk assessment, gap analysis, and cybersecurity program development
- Hands-on experience with incident response, including AI-related threat scenarios
- Proficiency in scripting, automation, and API integrations
- Experience working with Security Engineering, SOC, or Forensics teams
Certifications (Preferred):
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CISSP, CISM, GIAC, CEH, GCIH, GCFE, GXPN, CISSP-ISSAP, SABSA, or equivalent AI-focused certifications (nice to have):
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Certified AI Security / ML Security certifications.
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Cloud provider AI/ML specialty certifications.
Benefits & conditions
- 401(k).
- Dental Insurance.
- Health insurance.
- Vision insurance.
- We are an equal-opportunity employer and value diversity, equality, inclusion, and respect for people.
- The salary will be determined based on several factors, including, but not limited to, location, relevant education, qualifications, experience, technical skills, and business needs.
