Principal Information Security Engineer

About Lumen

Lumen connects the world. We are igniting business growth by connecting people, data and applications – quickly, securely, and effortlessly. Together, we are building a culture and company from the people up – committed to teamwork, trust and transparency. People power progress.

 

We’re looking for top-tier talent and offer the flexibility you need to thrive and deliver lasting impact. Join us as we digitally connect the world and shape the future.

The Role

The Principal AI Security Engineer is responsible for designing, governing, and advancing Lumen’s enterprise AI security program and internal AI driven security capabilities and innovations. This role operates at the intersection of AI/ML systems, cybersecurity architecture, governance, advanced defensive capability and innovation development.  This role ensures that AI technologies are deployed securely, responsibly, and at enterprise scale and utilized to protect the company. 

This role has direct accountability for AI security design and evolution, including AI enhanced threat detection, deepfake and synthetic media detection, security assistants, autonomous security agents, AI powered decision support systems, and other innovative solutions.

The Principal AI Security Engineer serves as a technical authority, partnering with the architecture team to set guiding principals, defining control patterns, and ensure alignment across AI Security Engineering, Governance, Architecture, Attack Surface Management, DevOps, Cyber Defense, Red Team, and Security Operations.

The Main Responsibilities

AI Security - Defense in Depth Strategy

 

• Engineer and maintain enterprise AI security controls, reference patterns, and control baselines securing AI/ML systems end to end, including software components, models, data flows, and runtime platforms.  
• Engineer integrations that enable continuous discovery, authoritative inventory, lineage tracking, and policy enforcement across AI development and operational environments.  
• Ensure AI security capabilities align with Responsible AI, data governance, and enterprise security policies, supporting auditability and governance approvals.  

 

AI Internal Capability Development

 

• Design and guide the development of AI enhanced threat and anomaly detection capabilities, including detection of AI generated attack patterns, model misuse, and data poisoning attempts.  
• Build deepfake and synthetic media detection solutions across text, audio, image, and video modalities to support fraud prevention, social engineering defense, and brand protection.  
• Establish secure baselines and framework for AI security assistants that support cross-functional security teams, especially those in operations.   Document and build summarization, triage assistance, threat interpretation, and automated guidance.  
• Design autonomous and semi autonomous AI security agents capable of executing chained security tasks (evidence gathering, enrichment, validation), ensuring governance guardrails, human in the loop controls, and approval workflows.  
• Enable AI powered security automation and decision support, including AI driven prioritization, risk scoring, remediation recommendations, and fix validation.  
• Support AI augmented threat hunting, red teaming and security research by enabling controlled generative AI use for adversarial testing, prompt injection simulation, and model jailbreak scenario generation.  
• Governance, Risk, and Cross Functional Leadership
• Act as a senior technical advisor to AI Governance, Data Governance, and Architecture Review Boards on AI risk, controls, and acceptable use.  
• Partner with architecture, DevOps and application teams to embed AI security controls into CI/CD pipelines and runtime environments.  
• Collaborate with Red Team / Offensive Security to ensure adversarial testing aligns with enterprise AI security architectures and emerging threat models.  
• Provide executive level reporting and technical narratives on AI security posture, capability maturity, and emerging risks.  

What We Look For in a Candidate

Required Technical Expertise:

 

AI & ML Security

 

• Deep understanding of AI/ML systems, including model training, inference pipelines, orchestration frameworks, and agent based systems.  
• Expertise in AI specific threat classes, including prompt injection, data leakage, data poisoning, model extraction, adversarial inputs, and jailbreak techniques.
• Experience securing generative AI, multimodal models, and agentic AI systems in enterprise environments.