Consulting Director, AI Security

Veriipro; Chicago (IL); On-site; USD 180,000 - 240,000; Full time

Job summary

Veriipro in Chicago seeks an experienced AI security architect to define and evolve security strategy for AI, cloud, and data pipelines, aligned with risk tolerance. You will lead threat modeling and secure architecture across cloud environments.

The role requires deep expertise in AI/ML security, cloud security architectures, and DevSecOps, with strong communication to executives and cross-functional teams.

Qualifications

• 10+ years of information security experience including cloud and AI/ML.
• Experience with public cloud security (AWS, Google Cloud).
• Relevant certifications preferred (CISSP, CCSP, etc.).
• Insurance or financial services experience preferred.
• Expert knowledge of AI/ML, GenAI, and LLM security concepts.
• Deep expertise in cloud security architecture (AWS, Google Cloud).
• Hands-on security across multiple domains (data, application, identity, endpoint).
• Strong DevSecOps and secure SDLC understanding.
• Understanding of global regulations and risk governance, privacy concepts.
• Ability to translate technical risks into business insights.
• Executive communication and independent work capabilities.

Responsibilities

• Define and evolve AI security strategy, roadmap, and architecture aligned to business objectives and risk tolerance.
• Design and implement secure AI and cloud-native security architectures using defense-in-depth.
• Lead threat modeling, risk assessments, and security evaluations of AI systems and data pipelines.
• Integrate AI security controls into SDLC, CI/CD, and DevSecOps practices.
• Establish AI security frameworks aligned to industry standards (NIST, OWASP) and enterprise policies.
• Develop AI security policies, standards, and best practices.
• Partner with Legal, Risk, and AI Governance on compliance and regulatory requirements.
• Provide guidance on securing AI workloads across cloud environments (e.g., Google Cloud).
• Serve as enterprise SME and a point of contact for AI security.
• Evaluate AI security tools and support monitoring, vulnerability management, and incident readiness.

Skills

Information security

Cloud security

AI/ML security

DevSecOps

Regulatory & privacy

Executive communication

Independent work

Program & project mgmt

Certifications

Risk to business insights

Cloud architectures

Job description

Must-Have Technical/Functional Skills

• 10+ years of information security experience, including cloud and AI/ML.
• Experience with public cloud security (AWS, Google Cloud).
• Relevant certifications preferred (CISSP, CCSP, etc.).
• Insurance or financial services experience preferred.
• Expert knowledge of AI/ML, GenAI, and LLM security concepts.
• Deep expertise in cloud security architecture (AWS, Google Cloud).
• Well-rounded cybersecurity knowledge and hands-on experience with multiple domains of security
• [including Data Security, Application Security, Identity Security, Endpoint Security, etc].
• Strong understanding of DevSecOps and secure software development.
• Understanding of global regulations and corresponding risk governance, legal and privacy aspects.
• Ability to translate technical risks into business insights.
• Strong communication and influencing skills, with executive presence.
• Ability to work independently in complex environments.
• Strong program and project management capabilities.

Roles & Responsibilities

• Define and evolve AI security strategy, roadmap, and architecture aligned to business objectives and risk tolerance.
• Design and implement secure AI and cloud-native security architectures using defense-in-depth principles.
• Lead threat modeling, risk assessments, and security evaluations of AI systems and data pipelines.
• Integrate AI security controls into SDLC, CI/CD, and DevSecOps practices.
• Establish AI security frameworks aligned to industry standards (e.g., NIST, OWASP) and enterprise policies.
• Develop AI security policies, standards, and best practices.
• Partner with Legal, Risk, and AI Governance on compliance and regulatory requirements.
• Provide guidance on securing AI workloads across cloud environments (e.g. Google Cloud).
• Serve as enterprise SME and a point of contact for AI security.
• Evaluate AI security tools and support monitoring, vulnerability management, and incident readiness.