Define and implement enterprise-wide AI governance frameworks to ensure responsible, ethical, and compliant use of AI in financial operations.
Develop and enforce AI security standards aligned with regulatory requirements (e.g., FFIEC, OCC, GLBA, GDPR, ISO 42001, NIST AI RMF).
Partner with risk, compliance, and legal teams to create policies covering AI model lifecycle management, bias detection, explainability, and auditability.
Oversee secure AI/ML solution deployment in both on-premises and cloud environments (AWS, Azure, GCP), ensuring robust data protection and encryption practices.
Conduct AI security risk assessments, threat modeling, and red team testing for generative AI and predictive models.
Establish monitoring frameworks for AI systems to track drift, anomalies, and adversarial threats.
Provide architectural guidance on integrating AI platforms with existing banking systems (ACH, RTP, Wires, Core Banking, Payment Hubs).
Lead AI security incident response and ensure remediation processes meet financial regulatory standards.
Serve as a subject matter expert for internal stakeholders on AI governance, regulatory compliance, and ethical AI adoption.
Mentor junior architects and engineers in AI governance and cybersecurity best practices.

Requirements

Bachelor’s degree in Computer Science, Cybersecurity, Data Science, or related field and at least 7 years of professional experience in enterprise architecture, information security, or technology governance in financial services, OR equivalent combination of education and work experience.
Proven track record of implementing governance frameworks, risk management strategies, and compliance programs for emerging technologies.
Familiarity with financial services regulations and security requirements.
Experience collaborating with auditors, regulators, and compliance teams.
Strong understanding of AI/ML lifecycle management, including model development, validation, deployment, and monitoring.
Knowledge of data governance principles, MDM (Golden Record, Canonical Models), and regulatory compliance in financial services.
Proficiency in cloud-native AI/ML platforms (AWS SageMaker, Bedrock, Azure AI, GCP Vertex).
Familiarity with security frameworks (NIST, ISO 27001/42001, CIS Controls).
Ability to translate complex AI and security concepts into business-friendly language.

Benefits

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI governance frameworksAI security standardsAI model lifecycle managementbias detectionexplainabilityauditabilityAI/ML solution deploymentdata protectionencryption practicesrisk assessments

Soft Skills

leadershipmentoringcommunicationcollaborationproblem-solvingsubject matter expertisepolicy developmentstrategic thinkingadaptabilitytranslating complex concepts

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in CybersecurityBachelor’s degree in Data ScienceISO 27001ISO 42001NIST AI RMF