Lead Cybersecurity - Application Security Architect – AI Models, Frameworks & Implementation

Application Security Architect

Join AT&T and reimagine the communications and technologies that connect the world. Our Chief Security Office ensures that our assets are safeguarded through truthful transparency, enforce accountability and master cybersecurity to stay ahead of threats. Bring your bold ideas and fearless risk-taking to redefine connectivity and transform how the world shares stories and experiences that matter. When you step into a career with AT&T, you won't just imagine the future-you'll create it.

We are seeking an Application Security Architect to secure the design, development, integration, and operation of AI/ML-enabled applications, including LLMs, agent-based systems, RAG pipelines, model-serving APIs, and AI orchestration frameworks, as well as advance the vulnerability management program as it relates to AI based vulnerabilities. This role combines application security architecture with AI security engineering to reduce risk across the full AI lifecycle – from data ingestion and model integration to inference-time protections and production governance – and lead AI Security from a vulnerability management and risk-reduction perspective.

This role is primarily focused on identifying, assessing, prioritizing, and helping remediate security weaknesses across AI-enabled applications, services, models, and integration patterns in order to reduce exploitability and accelerate remediation.

The ideal candidate combines strong Application Security expertise with practical experience securing AI/ML systems, LLM-based applications, agentic workflows, and model integrations. This individual should understand both traditional App Sec principles and AI-specific attack patterns and be able to apply that knowledge to improve vulnerability discovery, risk triage, security testing, architecture review, and remediation guidance across the AI lifecycle.

We are looking for a technically minded, hands-on security architect who can evaluate AI implementations for real security risk, define effective controls, partner with engineering teams to remediate issues, and improve how AI-related vulnerabilities are managed across development and production environments. The right candidate will also bring coding aptitude and implementation experience to support secure development workflows, integrate security checks and automation, implement security controls in applications and pipelines, and build practical solutions where necessary to improve coverage, consistency, and speed.

This role is unique because it sits at the intersection of Application Security, AI/ML architecture, and hands-on security engineering. It is not a traditional security governance role, and it is not purely an AI engineering role. We are looking for someone who can bridge both worlds: a candidate who understands how applications are built and attacked, how AI systems are integrated and abused, and how to translate that into secure architecture, practical controls, and scalable implementation patterns.

This role is an opportunity to shape how AI is adopted securely across the organization by influencing architecture, standards, implementation, and operational guardrails from the ground up. The ideal candidate will help define the future state of AI-enabled application security while also remaining close enough to the technology to validate designs, code solutions where needed, and solve real-world security problems.

Typical Goals (30/60/90 Days):

• Inventory current AI-enabled applications, model integrations, third-party AI services, and major use cases.
• Build an initial view of the organization's AI attack surface and identify the highest-risk applications or integration patterns.
• Meet with key stakeholders across App Sec, architecture, AI/ML, engineering, platform, and risk functions to understand current capabilities and gaps.
• Review existing standards, deployment patterns, and known AI-related risks.

• Establish and socialize a lightweight AI threat modeling and secure architecture review process.
• Publish baseline AI application security standards and secure implementation guidance.
• Prioritize top AI security control gaps and…