& Strategy
- Design and maintain secure, scalable, and resilient security architectures across AWS, Azure, and GCP.
- Define cloud and AI security reference architectures, patterns, and standards covering IaaS, PaaS, containers, serverless, and AI platforms.
- Lead security architecture reviews for cloud and AI initiatives, ensuring consistency, defense-in-depth, and least-privilege design.
- Managed AI services (e.g., Amazon Bedrock, Azure OpenAI, GCP Vertex AI), self-hosted and open-source models
Identity, Network, and Data Security
- Architect IAM strategies for cloud and AI services (human, workload, and service identities).
- Design network security architectures (segmentation, private endpoints, service perimeters, Zero Trust).
- Define data protection and key management strategies for cloud and AI workloads, including encryption, KMS/HSM, BYOK/HYOK, and secrets management.
Risk Management, Compliance & AI Governance
- Ensure cloud and AI architectures align with security and compliance frameworks (NIST, ISO 27001, SOC 2, CIS, GDPR, etc.).
- Contribute to AI governance programs, including:
- Responsible AI and ethical AI principles
- Model risk management and lifecycle controls
- Compliance with emerging AI regulations and standards (e.g., NIST AI RMF, EU AI Act readiness)
- Support threat modeling, risk assessments, and control mapping for both cloud and AI systems.
Security Engineering & Automation (DevSecOps / MLOps)
- Embed security into CI/CD and MLOps pipelines for cloud and AI workloads.
- Promote infrastructure-as-code and policy-as-code for consistent security enforcement.
- Define detection and response strategies using cloud-native and AI-aware security tooling, including logging, SIEM integration, and anomaly detection.
Leadership & Collaboration
- Serve as a senior security authority and trusted advisor for cloud, platform, data, and AI engineering teams.
- Mentor engineers and architects on cloud and AI security best practices.
- Evaluate and recommend cloud, AI, and security platforms and third-party solutions.
Required Qualifications
Experience
- 8+ years of experience in cloud security architecture, security engineering, or related roles.
- Demonstrated experience securing multi-cloud environments (AWS, Azure, GCP).
- Hands-on experience designing security controls for AI/ML or GenAI workloads in production environments.
Certifications (Required)
- CISSP (Certified Information Systems Security Professional)
- CCSP (Certified Cloud Security Professional)
- Cloud security certifications, such as:
- AWS Certified Security - Specialty
- Microsoft Certified: Azure Security Engineer (Associate or Expert)
- Google Professional Cloud Security Engineer
Technical Skills
- Deep expertise in:
- Cloud IAM, networking, logging, and security services
- Encryption, PKI, KMS/HSM, and secrets management
- Kubernetes and container security
- Strong understanding of:
- AI/ML pipelines, GenAI architectures, and model lifecycle
- AI-specific threat models and mitigations
- DevSecOps and secure MLOps practices
Preferred Qualifications
- Experience securing regulated or high-risk environments (financial services, healthcare, government).
- Familiarity with Zero Trust and privacy-enhancing technologies.
- Knowledge of AI governance frameworks (NIST AI RMF, ISO/IEC 23894, EU AI Act).
- Strong communication skills with the ability to influence both technical and executive stakeholders.
The annual salary range for California is $185,500 to $344,500. You may also be eligible to receive incentive compensation: bonus, equity, and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the salary range is a guideline and compensation may vary based on factors such as qualifications, skill level, competencies and work location. Our benefits programs include: paid vacation and paid holidays, 401(k) plan with employer match, employee stock purchase plan, a variety of medical, dental and vision plan options, and more.
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