Principal Engineer – AI Security

Jobtailor; Brooklyn Park (MN); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

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Job summary

Jobtailor in Minnesota is seeking an senior AI security architect to lead risk assessment and validation across AI platforms and workflows. You will partner with platform, product, and engineering teams to drive secure deployment patterns in cloud and hybrid environments, and guide on model security and data protection.

Required are 10+ years in tech, strong expertise in LLM security, OWASP Top 10 for LLM apps, and experience with GCP/AWS/Azure.

Qualifications

• 4-year degree OR equivalent experience.
• Polyglot programmer comfortable in many languages across different platforms.
• 10+ years of hands-on experience in technology.
• Extensive knowledge of cybersecurity domains including Information Protection, Cloud Security (GCP strongly preferred), Networking Security, IAM, Automation, and SIEM.
• LLM Security expertise (RAG, MCP, input validation, sandboxing, etc.)
• In-depth understanding of OWASP Top 10 for Large Language Model Applications
• Expertise in AI and ML
• Understanding of prompt injection and its various styles (direct, indirect, RAG poisoning, etc.)
• Understanding of MCP auth patterns including dynamic client registration
• Knowledge of RAG authorization patterns and RBAC implementation in RAG
• Understanding of OAuth roles and flows and minimizing risky permissions
• Experience mitigating the security risks of local coding agents
• Solid understanding of containerization technologies and tools
• Demonstrated curiosity and ability to learn
• Stays current on relevant technologies with self-directed learning
• Excellent written and verbal interpersonal skills with strong presentation abilities
• Proven history of utilizing a variety of security tools and technologies across diverse environments
• Good understanding of security management workflows in large enterprise organizations and complex environments
• Good understanding of the current threat landscape
• In-depth knowledge of security frameworks, standards, and best practices, e.g. NIST and ISO/IEC 27001
• Strong understanding of network security, cryptography, and secure software development
• Experience with firewalls, IDS/IPS, SIEM, and DLP
• Excellent analytical, problem-solving, and communication skills
• Preferred: GCP native security product experience, LLM Security expertise, Vertex AI experience, AWS or Azure experience

Responsibilities

• Collaborate with AI platform, product, and engineering teams to evaluate AI systems throughout their lifecycle
• Assess AI architectures, models, agents, and supporting infrastructure for security risks, vulnerabilities, and design weaknesses
• Develop and execute security validation strategies, including threat modeling, attack simulation, and adversarial testing
• Evaluate security controls, guardrails, and mitigations protecting AI applications and platforms
• Identify emerging AI-specific threats, attack techniques, and vulnerabilities and communicate business impact
• Recommend risk mitigation strategies and prioritized remediation plans
• Conduct technical reviews of AI products, platforms, and architectures
• Partner with engineering teams to validate secure deployment patterns across cloud and hybrid environments
• Define security assessment methodologies, testing frameworks, and assurance standards
• Provide guidance on model security, prompt injection defenses, agent security, supply chain security, and data protection
• Prioritize security improvements that reduce risk while enabling innovation and business objectives
• Perform hands-on security analysis and testing of complex AI-enabled systems
• Improve AI security controls and governance practices with security, architecture, and engineering teams
• Assess and communicate security risks to stakeholders
• Serve as a trusted advisor on AI security across the enterprise

Skills

LLM Security Expertise

Cloud Security

Cybersecurity Domains Knowledge

Threat Modeling

Adversarial Testing

OWASP Top 10 Knowledge

Containerization Technologies

Security Frameworks Knowledge

Risk Mitigation Strategies

Secure Software Development

Data Protection

Education

4-year degree or equivalent experience

Tools

SIEM

Firewalls

IDS/IPS

DLP

GCP Native Security Products

Vertex AI

AWS

Azure

Job description

• Collaborate with AI platform, product, and engineering teams to evaluate AI systems throughout their lifecycle
• Assess AI architectures, models, agents, and supporting infrastructure for security risks, vulnerabilities, and design weaknesses
• Develop and execute security validation strategies, including threat modeling, attack simulation, and adversarial testing
• Evaluate security controls, guardrails, and mitigations protecting AI applications and platforms
• Identify emerging AI-specific threats, attack techniques, and vulnerabilities and communicate business impact
• Recommend risk mitigation strategies and prioritized remediation plans
• Conduct technical reviews of AI products, platforms, and architectures
• Partner with engineering teams to validate secure deployment patterns across cloud and hybrid environments
• Define security assessment methodologies, testing frameworks, and assurance standards
• Provide guidance on model security, prompt injection defenses, agent security, supply chain security, and data protection
• Prioritize security improvements that reduce risk while enabling innovation and business objectives
• Perform hands-on security analysis and testing of complex AI-enabled systems
• Improve AI security controls and governance practices with security, architecture, and engineering teams
• Assess and communicate security risks to stakeholders
• Serve as a trusted advisor on AI security across the enterprise

Requirements

• 4-year degree OR equivalent experience
• Polyglot programmer comfortable in many languages across different platforms
• 10+ years of hands-on experience in technology
• Extensive knowledge of cybersecurity domains including Information Protection, Cloud Security (GCP strongly preferred), Networking Security, IAM, Automation, and SIEM
• LLM Security expertise (RAG, MCP, input validation, sandboxing, etc.)
• In-depth understanding of OWASP Top 10 for Large Language Model Applications
• Expertise in AI and ML
• Understanding of prompt injection and its various styles (direct, indirect, RAG poisoning, etc.)
• Understanding of MCP auth patterns including dynamic client registration
• Knowledge of RAG authorization patterns and RBAC implementation in RAG
• Understanding of OAuth roles and flows and minimizing risky permissions
• Experience mitigating the security risks of local coding agents
• Solid understanding of containerization technologies and tools
• Demonstrated curiosity and ability to learn
• Stays current on relevant technologies with self-directed learning
• Excellent written and verbal interpersonal skills with strong presentation abilities
• Proven history of utilizing a variety of security tools and technologies across diverse environments
• Good understanding of security management workflows in large enterprise organizations and complex environments
• Good understanding of the current threat landscape
• In-depth knowledge of security frameworks, standards, and best practices, e.g. NIST and ISO/IEC 27001
• Strong understanding of network security, cryptography, and secure software development
• Experience with firewalls, IDS/IPS, SIEM, and DLP
• Excellent analytical, problem-solving, and communication skillsPreferred: GCP native security product experience, LLM Security expertise, Vertex AI experience, AWS or Azure experience

Core Competencies

Demonstrates extensive expertise in AI and ML security, including LLM Security, threat modeling, and risk mitigation strategies. Proficient in evaluating and enhancing security controls across cloud environments, with a strong understanding of cybersecurity frameworks and best practices.

Highest-signal resume keywords

• LLM Security Expertise
• Cloud Security (GCP Preferred)
• Cybersecurity Domains Knowledge
• Security Assessment Methodologies
• Network Security Understanding

Hard Skills

• Polyglot Programming
• Cybersecurity
• Threat Modeling
• Adversarial Testing
• OWASP Top 10 Knowledge
• Containerization Technologies
• Security Frameworks Knowledge
• Risk Mitigation Strategies
• Secure Software Development
• Data Protection

Soft Skills

• Excellent Communication Skills
• Analytical Problem-Solving
• Interpersonal Skills
• Curiosity and Self-Directed Learning
• Presentation Abilities

Industry Keywords

• Information Protection
• IAM
• Networking Security
• Automation
• Security Management Workflows
• Current Threat Landscape
• NIST
• ISO/IEC 27001
• RBAC Implementation
• OAuth Roles and Flows

Tools & Technologies

• SIEM
• Firewalls
• IDS/IPS
• DLP
• GCP Native Security Products
• Vertex AI
• AWS
• Azure