Specialist Cybersecurity - Control Testing - Technology Risk / Sox / Pcidss

AT&T AT&T · Telecom · Bangalore, KA, India

This role focuses on testing IT and security controls within AT&T's technology services, with a specific emphasis on regulatory compliance (SOX, PCIDSS). While the role requires familiarity with AI/ML in cybersecurity and experience with AI-enabled tools, its core function is control testing and risk management, not the direct development or deployment of AI models as a primary deliverable. The role aims to enhance existing security operations and risk assessment processes through the application of AI tools and understanding of AI-driven risks.

What you'd actually do

  1. Partner with ATS leadership to evaluate the criticality of AT&T’s infrastructure, applications, and projects, and identify high‑risk areas for deep dive reviews.
  2. Develop targeted test plans for each review, leveraging recent IT control test results and relevant risk findings.
  3. Execute deep dive reviews, identify issues requiring remediation, and report them to ATS stakeholders with clear risk articulation.
  4. Supporting periodic articulation of risk to ATS’s objectives using the test results and open issues by the Reporting team.
  5. Contribute to the development and enhancement of the Testing Methodology, TRMF components, and tooling related to control testing.

Skills

Required

  • 8 years minimum experience in technology risk management or consulting with at least 5 years in design or testing of controls focused on critical IT infrastructure and applications.
  • Strong understanding of various technology risk management frameworks and standards.
  • Strong exposure to regulatory requirements in multiple industries like SOX, PCIDSS etc.
  • Familiarity with applying Artificial Intelligence (AI) or Machine Learning (ML) techniques in cybersecurity contexts (e.g., anomaly detection, threat hunting, behavioral analytics, or risk scoring).
  • Experience leveraging AI-enabled tools (such as Copilot for Security, Darktrace, CrowdStrike Charlotte AI, or custom LLM integrations) to enhance detection, response, and automation workflows.
  • Exposure to data science fundamentals relevant to security (pattern recognition, supervised vs. unsupervised learning, model validation).
  • Awareness of AI-driven risks (e.g., adversarial ML, data poisoning, model hallucination) and their mitigation within enterprise environments.

Nice to have

  • Understanding of LLM safety, prompt engineering, or AI governance frameworks (e.g., NIST AI RMF, EU AI Act readiness) is a plus.
  • Bachelors or Master’s degree in computer science, Mathematics, Information Systems, Engineering or Cyber Security.
  • Flexible and creative thinker with strong execution skills.
  • Prior experience with Telecom sector
  • ISACA, ISC2 or other relevant certifications

What the JD emphasized

  • SOX
  • PCIDSS
  • critical IT infrastructure and applications
  • AI/ML techniques in cybersecurity contexts
  • AI-enabled tools
  • AI-driven risks