Agentic AI Cybersecurity Engineer

Responsibilities

• Design and enhance automated metrics for control effectiveness and continuous control monitoring.
• Develop, configure, test, and maintain AI-enabled agents and automation workflows for evidence evaluation, exception identification, remediation recommendations, and self-auditing.
• Source, validate, and transform data for automated control testing and agent-driven analysis.
• Analyze control testing outputs, cybersecurity telemetry, and agent findings to identify trends, anomalies, risks, and control improvements.
• Build dashboards, reports, and data products covering control health, self-audit results, exceptions, and operational risk.
• Define and track KPIs and KRIs including control trends, exception volumes, agent findings, remediation timeliness, and self-audit coverage.
• Improve control documentation, data integrity, control standardization, automated testing, monitoring, and reporting under the RCSA framework.
• Design secure and governed AI agents and workflows aligned with security standards, risk requirements, data protection, control objectives, and responsible AI practices.
• Create prompts, rules, workflows, orchestration logic, validation criteria, and feedback loops for control implementation, self-audits, exception triage, remediation tracking, and evidence analysis.
• Support security controls and monitoring for AI-enabled applications and workflows.

Requirements

• At least 2 years of experience in cybersecurity, control management, technology risk, audit response, automation engineering, or related disciplines.
• Experience with automated control testing, continuous control monitoring, automated evidence review, or self-audit capabilities.
• Knowledge of generative AI risks, model integrity, prompt security, data protection, responsible AI, and AI-assisted cybersecurity operations.
• Experience creating or configuring AI agents, automation frameworks, or agentic AI workflows for monitoring, detection, control validation, evidence analysis, and security engineering.
• Ability to translate control objectives into executable agent tasks for evidence collection, test execution, exception identification, summarization, and escalation.
• Strong engineering ability to turn control requirements into automated logic, repeatable tests, data pipelines, dashboards, and agent-enabled workflows.
• Understanding of RCSA control processes, operational risk management, control design, evidence expectations, and audit readiness.
• Experience using Python, SQL, APIs, workflow automation, analytics tools, Excel, and PowerPoint for control monitoring and reporting.
• Strong proficiency with Confluence, SharePoint, Slack, or Teams.
• Bachelor’s degree in Computer Science, Information Systems, Cybersecurity, Engineering, or Data Analytics, or comparable experience.
• Employment eligibility to work with American Express in the United States is required.