AI Security Architect: Secure ML & Cloud Workloads

Cadence Design Systems; San Jose (CA); On-site; USD 164,500 - 305,500; Full time

Benefits offered by this job

Bonus

Equity

Paid vacation

401(k) match

Job summary

Cadence Design Systems' InfoSec team is seeking a Security Architect to design, implement, and govern secure AI systems across the enterprise, focusing on training, inference, and deployment pipelines.

You will lead threat modeling, data protection, and cloud security for AI workloads across major cloud providers, collaborate with data scientists and ML engineers, and help drive governance, standards, and audits.

Qualifications

• Bachelor's or Master's degree in Computer Science, Cybersecurity, or related field.
• 8+ years in cybersecurity architecture or engineering.
• Experience securing AI/ML systems or data platforms.
• Strong cloud security, API security, encryption, and IAM expertise.

Responsibilities

• Design secure AI/ML architectures for training, inference, and deployment pipelines.
• Model threat modeling and risk management aligned with AI risk frameworks.
• Protect training and inference data and implement governance and encryption.
• Secure AI workloads across cloud platforms and integrate securely with AI services.
• Monitor models for drift, abuse, and security; manage access and versioning.
• Develop AI security policies, standards, and governance; support audits.
• Collaborate with data scientists and ML engineers; lead security reviews.

Skills

AI Threat Modeling

Secure MLOps

Zero Trust Architecture

Data Privacy & Governance

Cloud-native security

Risk & Compliance management

Education

Bachelor's or Master's degree in Computer Science, Cybersecurity, or related field

Tools

SageMaker

Kubeflow

MLflow

SIEM/XDR platforms

Job description

Cadence Design Systems' InfoSec team is seeking a Security Architect to design, implement, and govern secure AI systems across the enterprise, focusing on training, inference, and deployment pipelines.

You will lead threat modeling, data protection, and cloud security for AI workloads across major cloud providers, collaborate with data scientists and ML engineers, and help drive governance, standards, and audits.