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.Skills Required
- Bachelor's or Master's degree in Computer Science, Cybersecurity, or a related field
- 8+ years of experience in cybersecurity architecture or engineering
- Experience securing AI/ML systems or data platforms
- Strong understanding of cloud security, including IAM, networking, containers, and serverless technologies
- Strong understanding of API security and microservices
- Experience with encryption, key management, and identity systems
- Experience developing Agent and Agentic AI for security use cases
- Experience with MCP
- Experience with LLMs, prompt engineering, or RAG architectures
- Familiarity with adversarial machine learning techniques
- Knowledge of MLflow, Kubeflow, or SageMaker
- Knowledge of SIEM or XDR platforms
- CISSP, CCSP, or cloud security certifications
- Experience in the semiconductor industry
Cadence Design Systems Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cadence Design Systems and has not been reviewed or approved by Cadence Design Systems.
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Equity Value & Accessibility — A discounted ESPP with a lookback feature and equity included in total compensation make ownership broadly accessible and potentially meaningful. Structured compensation at an industry leader adds predictability to equity participation.
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Healthcare Strength — Medical, dental, and vision coverage are described as solid, with mental‑health/EAP and fertility support enhancing the offering. The breadth across core care and family‑building needs strengthens the healthcare package.
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Leave & Time Off Breadth — Global Recharge Days, volunteer time off, and companywide breaks indicate a comprehensive time‑off framework. In addition, many salaried roles are described as having flexible or generous PTO policies.
Cadence Design Systems Insights
What We Do
Cadence enables electronic systems and semiconductor companies to create the innovative end products that are transforming the way people live, work and play. Cadence® software, hardware and IP are used by customers to deliver products to market faster. The company's Intelligent System Design strategy helps customers develop differentiated products—from chips to boards to intelligent systems—in mobile, consumer, cloud, data center, automotive, aerospace, IoT, industrial and other market segments. Cadence is listed as one of Fortune Magazine's 100 Best Companies to Work For.

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