Cyber AI Security Manager

Crowe•Chicago, IL

5d•Remote

About The Position

The Cyber AI Security Manager sits at the intersection of AI engineering and cybersecurity. You will help clients securely adopt AI while also helping Crowe reinvent how cybersecurity services are delivered using AI. You will assess and secure GenAI, ML, and agentic systems, develop security patterns and controls for emerging AI architectures, and partner with cybersecurity teams to identify, prototype, and scale AI-enabled capabilities that improve the speed, quality, and effectiveness of our client solutions.

Requirements

Minimum of 7 years' experience in cybersecurity, particularly focused on securing software and data-intensive products.
Proficiency with cybersecurity frameworks such as NIST, ISO 27001, or CIS Controls.
Familiarity with AI-specific regulatory environments and ethical considerations surrounding AI deployment.
Experience with AI related frameworks such as NIST AI RMF, OWASP Top 10 for LLM Applications / GenAI Security Project, and MITRE ATLAS.
Hands-on experience designing, developing, or integrating AI/ML or Generative AI solutions, including experience with LLM APIs, AI agents/tool use, and modern AI application architectures.
Demonstrated ability to identify cybersecurity use cases for AI and translate them into prototypes, production solutions, or scalable service offerings.
Deep understanding of AI/ML systems architecture and the associated security considerations.
Excellent communication skills, with the ability to clearly articulate complex security topics to both technical and non-technical audiences.
Proven ability to collaborate effectively with cross-functional teams including engineering, legal, compliance, and business stakeholders.
Would require readiness to travel domestically approximately 80% of the time to meet client needs.
Certifications such as CISSP, CEH, CompTIA Security+, or relevant Microsoft Azure security certifications.
Bachelor’s degree.

Nice To Haves

Strong experience in penetration testing, vulnerability assessments, and security incident response.
Hands-on experience with cloud security practices, especially within Microsoft Azure, including identity management, access controls, and secure networking configurations.
Proven expertise in GDPR compliance, SOC 2 audits, and handling of sensitive PII.
Experience with data anonymization techniques and privacy-preserving machine learning methodologies.
Understanding of DevSecOps principles and experience integrating security into CI/CD pipelines.
Previous experience within professional services or consulting environments, demonstrating client-facing capabilities and problem-solving skills.
Strong analytical and problem-solving skills, capable of navigating ambiguous scenarios and rapidly evolving threats.

Responsibilities

Collaborate closely with AI developers, DevOps engineers, and product teams to identify potential security vulnerabilities, implement best practices, and ensure compliance with regulatory standards.
Support security assessments, penetration testing, and vulnerability management for AI systems to proactively mitigate risks.
Act as the security expert in designing, developing, and deploying secure AI and machine learning applications, with a focus on safeguarding personally identifiable information (PII).
Stay ahead of emerging cybersecurity threats, privacy regulations, and compliance requirements to ensure that our AI solutions continuously meet and exceed market standards.
Document security protocols, conduct training sessions, and promote security awareness within the team and organization.
Engage with stakeholders across multiple disciplines to refine security policies and procedures specific to AI and ML products.
Identify opportunities to apply GenAI, agents, ML, and automation to improve cybersecurity services and client outcomes.
Prototype and productionize AI-enabled security capabilities—for example, accelerating security assessments, threat analysis, vulnerability prioritization, control testing, evidence analysis, or security operations.
Partner with cybersecurity practitioners to understand existing delivery processes and determine where AI can improve quality, speed, scalability, or insight.
Evaluate emerging AI security tooling and determine where commercial products versus custom AI solutions make sense.
Help establish reusable AI-enabled cybersecurity accelerators, patterns, and intellectual property that can be deployed across client engagements.