Cybersecurity Engineer – Identity Access Lifecycle Management

Jobtailor

Phoenix (AZ)

On-site

USD 110,000 - 150,000

Full time

3 days ago

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Job summary

Jobtailor in United States (Phoenix area) seeks an expert to design and scale AI-enabled automation for control testing and self-audits. You will build agent-driven workflows, validate data pipelines, and deliver risk-informed insights to control owners and leadership.

You will collaborate across data, engineering, and governance teams, maintaining documentation quality, metrics frameworks, and secure AI practices under RCSA guidelines.

Qualifications

Bachelor's degree required in a relevant field and eligible to work in the United States.
Experience designing or supporting automated control testing, continuous control monitoring, automated evidence review, or self-audit capabilities.
Knowledge of AI security concepts, including generative AI risks, 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.

Responsibilities

Design, build, 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 and remediation recommendations.
Partner with data, engineering, and technology teams to source, validate, and transform data for automated control testing and agent-driven analysis.
Define and track KPIs/KRIs including control performance trends, exception volumes, and self-audit coverage.
Engineer dashboards, reports, and data products providing visibility into control health and self-audit results.
Translate technical findings into risk-informed insights and recommendations for control owners, engineering partners, and leadership.

Skills

Python

SQL

AI Security Concepts

Automation Frameworks

Data Pipelines

Control Metrics Design

Anomaly Detection

Automated Testing Logic

Dashboard Engineering

Evidence Validation

Collaboration

Communication

Problem-Solving

Education

Bachelor's degree in Computer Science, Information Systems, Cybersecurity, Engineering, Data Analytics, or comparable experience

Tools

Confluence

SharePoint

Slack

Teams

Excel

PowerPoint

AI Tools

Analytics Tools

Job description

Design, build, 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 scalable self-auditing
Partner with data, engineering, and technology teams to source, validate, and transform data for automated control testing and agent-driven analysis
Define and track KPIs/KRIs including control performance trends, exception volumes, agent findings, remediation timeliness, and self-audit coverage
Analyze control testing outputs, cybersecurity telemetry, and agent-generated findings to identify trends, anomalies, emerging risks, and control improvement opportunities
Engineer dashboards, reports, and data products providing visibility into control health, self-audit results, exception patterns, and operational risk posture
Translate technical findings into risk-informed insights and recommendations for control owners, engineering partners, and leadership
Enhance documentation quality, data integrity, control standardization, metrics frameworks, automated testing logic, and reporting capabilities under the RCSA framework
Scale automated testing, monitoring, and agent-enabled self-audit solutions across controls
Create and implement secure, governed AI agents and workflows aligned with security standards, risk requirements, control objectives, data protection, and responsible AI practices
Design and refine prompts, rules, orchestration logic, validation criteria, and feedback loops for cybersecurity engineering, self-audits, exception triage, remediation tracking, evidence analysis, and security research
Improve threat detection, investigation efficiency, and operational observability using AI-enabled security tooling
Support security controls and monitoring practices for AI-enabled applications and workflows

Requirements

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 generative AI risks, 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
Ability to design agent workflows translating control objectives into executable tasks
Experience designing, building, testing, and governing AI agents or agentic workflows connected to enterprise data sources
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, control design, evidence expectations, and audit readiness
Experience automating data metrics, control testing, and self-audit processes
Understanding of AI/ML, NLP, and generative AI for control performance analysis and anomaly detection
Experience using AI tools for metric design, documentation review, evidence validation, exception analysis, and workflow automation
Ability to interpret and validate AI-generated outputs within risk, control, and governance contexts
Experience with Python, SQL, APIs, workflow automation, analytics tools, Excel, and PowerPoint
Proficiency with Confluence, SharePoint, Slack, or Teams
Knowledge of AI-assisted cybersecurity operations and automation frameworks
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; no visa sponsorship

Core Competencies

Demonstrates expertise in designing and implementing AI-enabled automation workflows and control testing processes, with a strong focus on cybersecurity principles and risk management. Proficient in translating technical findings into actionable insights while ensuring compliance with security standards and control objectives.

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