AI Security Architect

Cadence Design Systems; San Jose (CA); Hybrid; USD 165,000 - 306,000; Full time

Benefits offered by this job

Paid vacation

401(k) plan with employer match

Employee stock purchase plan

Medical, dental, and vision plans

Job summary

Cadence Design Systems is seeking a Security Architect with deep AI/ML security expertise to design, implement, and govern secure AI systems across the enterprise in California.

The role focuses on protecting AI/ML models, data pipelines, and GenAI apps from emerging threats while enabling safe innovation. You will partner with data scientists, ML engineers, and product teams to embed security into AI platforms and cloud workloads.

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 understanding of cloud security, API security, and data encryption.

Responsibilities

• Design secure architectures for AI/ML systems across training, inference, and deployment pipelines.
• Define security controls for LLMs, GenAI platforms, and AI APIs.
• Embed security into MLOps pipelines (DevSecOps for AI).
• Conduct threat modeling for AI systems (prompt injection, data leakage).
• Develop risk frameworks aligned with NIST AI RMF.

Skills

AI Threat Modeling

Secure MLOps

Data Privacy

Cloud Security

Risk & Compliance

Education

Bachelor’s or Master’s in CS/Cybersecurity

Tools

MLflow

Kubeflow

SageMaker

Job description

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology. Cadence InfoSec seeking a Security Architect with deep expertise in Artificial Intelligence (AI) and Machine Learning (ML) security to design, implement, and govern secure AI systems across the enterprise. This role will focus on protecting AI/ML models, data pipelines, and GenAI applications from emerging threats while enabling safe innovation.

Key Responsibilities

• AI/ML Security Architecture Design secure architectures for AI/ML systems, including model training, inference, and deployment pipelines
• Define security controls for LLMs (Large Language Models), GenAI platforms, and AI APIs
• Embed security into MLOps pipelines (DevSecOps for AI)
• Threat Modeling & Risk Management Conduct threat modeling for AI systems (e.g., prompt injection, model poisoning, data leakage)
• Develop risk frameworks aligned with NIST AI Risk Management Framework
• Identify and mitigate adversarial AI threats and abuse cases
• Data Security & Privacy Ensure protection of training and inference data (PII, PHI, proprietary data)
• Implement data governance, anonymization, and encryption strategies
• Ensure compliance with regulations (GDPR, HIPAA, etc.)
• Cloud & Platform Security Secure AI workloads across cloud platforms such as Amazon Web Service Microsoft Azure Google Cloud IBM Cloud Architect secure integrations with AI services and APIs
• Model Security & Integrity Protect against model theft, inversion, and extraction attacks
• Implement model monitoring for drift, anomalies, and abuse
• Ensure secure model storage, versioning, and access control
• Governance & Compliance Establish AI security policies, standards, and guardrails
• Align with industry AI frameworks such as ISO AI standards (e.g., ISO/IEC 42001)
• Support audit, regulatory, and CIO and CISO reporting
• Collaboration & Leadership Partner with data scientists, ML engineers, and product teams Provide security guidance for AI product development Lead security reviews and architecture boards Mentor security engineers on AI-specific threats

Required 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 understanding of: Cloud security (IAM, network, containers, serverless) API security and microservices Encryption, key management, and identity systems Development of Agent and Agentic AI for security use cases Experience with MCP

Preferred Qualifications

• Experience with LLMs (e.g., prompt engineering, RAG architectures)
• Familiarity with adversarial ML techniques
• Knowledge of tools like: MLflow, Kubeflow, SageMaker SIEM/XDR platforms
• Certifications: CISSP, CCSP, or cloud security certifications
• Experience in semiconductor industry is a plus

Key Skills

• AI Threat Modeling (Prompt Injection, Data Poisoning, Model Evasion)
• Secure MLOps / DevSecOps Zero Trust Architecture
• Data Privacy & Governance
• Cloud-Native Security
• Risk & Compliance Management

The annual salary range for California is $164,500 to $305,500. 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.

We’re doing work that matters. Help us solve what others can’t.

Cadence is committed to equal employment opportunity throughout all levels of the organization. Cadence is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, basis of disability, or any other protected class.