AI Security Architect

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

Benefits offered by this job

Paid vacation and holidays

401(k) plan with employer match

Employee stock purchase plan

Medical, dental and vision plan options

Job summary

Cadence is looking for a Security Architect with expertise in AI and ML security. This role is vital for designing secure AI systems and protecting against emerging threats across the enterprise.

The ideal candidate should have a strong background in cybersecurity architecture, cloud security, and experience securing AI systems. You'll lead initiatives around data protection, threat modeling, and compliance within a collaborative environment.

The role offers competitive compensation, aligned with California's high-tech industry standards, along with various benefits.

Qualifications

• 8+ years in cybersecurity architecture or engineering.
• Experience securing AI/ML systems or data platforms.
• Strong understanding of cloud security, API security, encryption, and identity systems.

Responsibilities

• Design secure architectures for AI/ML systems.
• Conduct threat modeling for AI systems.
• Ensure protection of training and inference data.

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

Education

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

Tools

MLflow

Kubeflow

SageMaker

SIEM/XDR platforms

Job description

Cadence InfoSec is 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

Compensation

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. 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.

Benefits

• 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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