AI Security Architect - Erlanger, KY

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified checked Jun 13, 2026

Salary

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401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

AI Security Architect - Erlanger, KY AI Security Architect - Erlanger, KY Position Summary ADM's Global Information & Cyber Security (GICS), Security Architecture & Engineering team is seeking an AI Security Architect with an Engineering/Analyst background. This role safeguards enterprise AI systems by applying Industry guidance on AI risk standards and principles. The position ensures secure, resilient, and compliant AI adoption across cloud and enterprise environments, focusing on confidentiality, integrity, availability, safety, and ethical use of AI/ML systems. The role proactively identifies and mitigates risks from adversarial machine learning, data poisoning, model leakage, and unauthorized access, while collaborating cross-functionally to build secure and trustworthy AI systems. Key Responsibilities - Consult, Recommend and Implement practices aligned with joint internal and external guidance, including understanding AI risks, securing the AI lifecycle, ensuring resilience, and establishing accountability. - Threat Modeling & Adversarial Testing: Conduct threat modeling for AI/ML models and pipelines, lead adversarial testing, red teaming, and stress testing on AI models. - Review current internal capabilities, process, tooling and provide strategic and tactical recommendations to meet requirements to Secure, Defend, Thwart for Ai capabilities. - Threat Detection & Response: Monitor AI systems for adversarial ML attacks, prompt injection, and misuse. - Documentation & Best Practices: Develop and maintain documentation for AI security best practices. - Cross-team Collaboration: Partner with AI engineers, architects, compliance officers, Technologists, and stakeholders to embed controls and guide secure AI development. - Continuous Improvement: Stay up to date with advancements in AI and automation technologies to continuously improve

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