AI Security Architect

SwiftCruit; 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

Job Overview

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.

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 (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 Services, 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 (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 (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 & Benefits

The annual salary range for California is $164,500 to $305,500. Eligible for incentive compensation: bonus, equity, and benefits. Benefits include paid vacation and paid holidays, 401(k) plan with employer match, employee stock purchase plan, and medical, dental, and vision plans.

Equal Employment Opportunity

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.