Principal Engineer – Secure AI

Jobtailor; Brooklyn Park (MN); On-site; USD 150,000 - 230,000; Full time

Job summary

Jobtailor is seeking a senior AI security leader to evaluate and strengthen the security posture of AI systems across their lifecycle. You will collaborate with platform, product, and engineering teams to design robust threat models, testing strategies, and mitigation plans for secure AI deployments.

The role requires deep expertise in AI/ML security, LLM applications, and modern cloud environments, with a track record of delivering practical, risk-based security improvements within large

Qualifications

• 4-year degree or equivalent experience.
• Polyglot programmer comfortable across languages.
• 10+ years in technology with cybersecurity domains including Information Protection, Cloud Security, Networking Security, IAM, Automation, and SIEM.
• LLM Security expertise (RAG, MCP, Input validation, Sandboxing).
• In-depth understanding of OWASP top 10 for Large Language Model Applications.
• Expertise in AI and ML.

Responsibilities

• Collaborate with AI platform, product, and engineering teams to evaluate the security posture of AI systems throughout their lifecycle.
• Assess AI architectures, models, agents, and supporting infrastructure to identify security risks, vulnerabilities, and design weaknesses.
• Develop and execute security validation strategies for AI systems, including threat modeling, attack simulation, and adversarial testing.
• Evaluate the effectiveness of existing security controls, guardrails, and mitigations protecting AI applications and platforms.
• Identify emerging AI-specific threats, attack techniques, and vulnerabilities, and communicate their potential business impact.
• Recommend risk mitigation strategies and prioritized remediation plans to improve the security and resilience of AI systems.
• Conduct deep technical reviews of AI products, platforms, and architectures to identify opportunities for security improvement.
• Partner with engineering teams to validate secure deployment patterns for AI workloads across cloud and hybrid environments.
• Define security assessment methodologies, testing frameworks, and assurance standards for AI technologies.
• Provide expert guidance on AI security best practices, including model security, prompt injection defenses, agent security, supply chain security, and data protection.
• Prioritize high-impact security improvements that measurably reduce risk while enabling innovation and business objectives.
• Perform hands-on security analysis and testing of complex AI-enabled systems, identifying gaps in architecture, implementation, and operational controls.
• Collaborate with security, architecture, and engineering teams to continuously improve AI security controls and governance practices.
• Efficiently assess and communicate security risks to stakeholders, balancing technical realities, business priorities, and organizational objectives.
• Serve as a trusted advisor on AI security, helping teams make informed decisions as AI capabilities evolve across the enterprise.

Skills

AI security

Security engineering

Threat modeling

Prompt injection defenses

RAG MCP

OWASP for LLMs

Cloud security

Network security

IAM

SIEM

Education

Bachelors degree or equivalent experience

Tools

GCP

Kubernetes

Docker

OWASP ZAP

Security monitoring tools

Job description

Responsibilities

• Collaborate with AI platform, product, and engineering teams to evaluate the security posture of AI systems throughout their lifecycle
• Assess AI architectures, models, agents, and supporting infrastructure to identify security risks, vulnerabilities, and design weaknesses
• Develop and execute security validation strategies for AI systems, including threat modeling, attack simulation, and adversarial testing
• Evaluate the effectiveness of existing security controls, guardrails, and mitigations protecting AI applications and platforms
• Identify emerging AI‑specific threats, attack techniques, and vulnerabilities, and communicate their potential business impact
• Recommend risk mitigation strategies and prioritized remediation plans to improve the security and resilience of AI systems
• Conduct deep technical reviews of AI products, platforms, and architectures to identify opportunities for security improvement
• Partner with engineering teams to validate secure deployment patterns for AI workloads across cloud and hybrid environments
• Define security assessment methodologies, testing frameworks, and assurance standards for AI technologies
• Provide expert guidance on AI security best practices, including model security, prompt injection defenses, agent security, supply chain security, and data protection
• Prioritize high‑impact security improvements that measurably reduce risk while enabling innovation and business objectives
• Perform hands‑on security analysis and testing of complex AI‑enabled systems, identifying gaps in architecture, implementation, and operational controls
• Collaborate with security, architecture, and engineering teams to continuously improve AI security controls and governance practices
• Efficiently assess and communicate security risks to stakeholders, balancing technical realities, business priorities, and organizational objectives
• Serve as a trusted advisor on AI security, helping teams make informed decisions as AI capabilities evolve 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, with 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)
• Familiarity with OWSAP top ten for LLMs
• Understanding of MCP auth patterns including dynamic client registration
• Knowledge in RAG authorization patterns – "How do you implement RBAC in a RAG?"
• Understanding of OAuth roles and flows, and how it pertains to minimizing risky permissions
• Experience mitigating the security risks of local coding agents
• Solid understanding of containerization technologies and tools
• Seeks out cross‑team collaboration opportunities
• 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 effectively utilizing a variety of security tools and technologies across diverse environments
• Good understanding of security management workflows in large enterprise organizations and complex environments
• Has a good understanding of the current threat landscape and the challenges that most organizations are facing
• In-depth knowledge of security frameworks, standards, and best practices (e.g., NIST, ISO/IEC 27001)
• Strong understanding of network security, cryptography, and secure software development
• Experience with security technologies, such as firewalls, IDS/IPS, SIEM, and DLP