Agentic AI Cybersecurity Engineer - Identity Access Lifecycle Managementgmt

Qualifications

• 2+ years of experience in cybersecurity, control management, technology risk, audit response, automation engineering, or related disciplines.
• Experience designing or supporting automated control testing, continuous control monitoring, automated evidence review, or self-audit capabilities.
• Knowledge of AI security concepts, including risks associated with generative AI, model integrity, prompt security, data protection, and responsible use of AI-enabled workflows.
• Experience creating or configuring AI agents, automation frameworks, or agentic AI workflows used to enhance monitoring, detection, control validation, evidence analysis, and security engineering outcomes.
• Ability to design agent workflows that translate control objectives into executable tasks, including evidence collection, test execution, exception identification, result summarization, and escalation routing.
• Experience designing, building, testing, and governing AI agents or agentic workflows that connect to enterprise data sources, execute control validation tasks, evaluate evidence, identify exceptions, summarize results, and support human-reviewed self-auditing of cybersecurity controls.
• Strong engineering mindset with the ability to translate control requirements into automated logic, repeatable tests, data pipelines, dashboards, and agent-enabled workflows.
• Understanding of RCSA control processes, operational risk management concepts, control design, evidence expectations, and audit readiness requirements.
• Demonstrated ability to recognize opportunities and deliver automation of data metrics, control testing, and self-audit processes to support control effectiveness.
• Understanding of how AI/ML, NLP, and generative AI can be used to analyze control performance data, detect anomalies, summarize evidence, and identify potential control gaps.
• Experience using AI tools to assist in metric design, documentation review, evidence validation, exception analysis, workflow automation, and efficiency improvements.
• Ability to interpret AI-generated outputs, validate accuracy, identify limitations, and apply findings within a risk, control, and governance context.
• Experience leveraging Python, SQL, APIs, workflow automation, and analytics tools and Excel, PowerPoint to build scalable control monitoring and reporting solutions.
• Strong proficiency with Amex collaboration platforms such as Confluence, SharePoint, Slack, or Teams.
• Knowledge of AI security concepts, including risks associated with generative AI, model integrity, prompt security, and protection of sensitive enterprise data.
• Knowledge of AI-assisted cybersecurity operations and automation frameworks used to enhance detection, response, and security engineering workflows.
• Bachelor’s degree required in Computer Science, Information Systems, Cybersecurity, Engineering, Data Analytics, or comparable experience.
• Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.