[Hiring] Senior AI Security Engineer @World Wide Technology

Role Description

World Wide Technology's Information Security organization is hiring a Senior AI Security Engineer to help secure the organization's AI and machine learning ecosystem and reduce risk across WWT-developed and WWT-operated AI systems. As a Senior AI Security Engineer, you'll be a hands-on technical contributor helping mature an evolving AI security function. Your focus is executing the highest-impact technical security work and enabling teams to build and deploy AI systems securely at speed through:

• Threat modeling
• Model and AI application security review
• Adversarial testing and red-teaming
• Security tooling and automation
• Vulnerability remediation across the AI/ML lifecycle

Beyond securing what we build, you'll help govern the safe adoption of AI across the enterprise, establishing standards for sanctioned AI use, evaluating third-party AI tools and vendors, and reducing the risk of shadow AI. You'll support our customer-facing teams, equipping them to educate customers on AI security best practices and serving as a technical resource in customer conversations. You'll also help grow the skills of those around you and act as a trusted AI security resource for teams across the organization.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Information Security, or a related field or equivalent hands-on experience.
• Minimum 8 years of experience in security engineering, information security, or related technical disciplines, with a demonstrated focus on securing AI/ML systems.
• Proven experience defining and executing enterprise security strategies.
• Experience and deep technical knowledge of how AI/ML technologies work.
• Deep familiarity with AI security frameworks (e.g., NIST AI RMF, MITRE ATLAS, OWASP).
• Experience securing organizational tool stacks including cloud-based, hybrid or on-prem solutions.
• Deep knowledge of AI related threats, risks and mitigation strategies.
• Strong foundation in core security principles—threat modeling, secure design, and identity and access control—applied to AI/ML systems and the infrastructure that supports them.
• Hands-on experience securing AI/ML systems, including practical AI red teaming against LLMs, agentic workflows, or RAG systems.
• Strong programming and scripting proficiency (e.g., Python) for building security tooling, automation, and test harnesses across the AI/ML lifecycle.
• Hands-on experience securing cloud and containerized environments (AWS, Azure, and/or GCP; Kubernetes and containers), including the infrastructure on which AI/ML workloads are trained, deployed, and served.
• Experience embedding security into MLOps and AI/ML development pipelines (and the CI/CD workflows that feed them), including model and dataset integrity checks, guardrail validation, and automated security testing.
• Proven ability to communicate complex security risk clearly to both technical and non-technical audiences, including engineers, leadership, and customers.
• Demonstrated experience mentoring engineers and serving as a senior technical authority and subject-matter expert.
• Hands-on offensive security and AI red-teaming experience targeting AI systems—including prompt injection, jailbreaks, data poisoning, model extraction, and agent/tool-abuse techniques—along with familiarity testing the web, API, and infrastructure layers these systems depend on.
• Applicants must be authorized to work in the United States without sponsorship.

Requirements

• Hands-on experience with AI/ML security tooling and AI security posture management (AI-SPM) platforms (e.g., Wiz AI-SPM, Protect AI, HiddenLayer, Lakera, or comparable model-scanning and guardrail solutions).
• Hands-on experience securing AI/LLM-enabled and agentic applications, including deep familiarity with OWASP Top 10 for LLM Applications, OWASP Top 10 for Agentic AI, MITRE ATLAS, NIST AI RMF, and Model Context Protocol (MCP) security implications.
• Practical experience with agent frameworks and orchestration (e.g., LangChain/LangGraph, CrewAI, AutoGen, or custom agent architectures) and with LLM evaluation, observability, and red-teaming tooling for testing model and agent behavior.
• Experience operating within governance, risk, and compliance frameworks, with exposure to enterprise AI adoption, third-party/vendor AI risk assessment, and AI policy or standards development.
• Experience in client-facing, consulting, or pre-sales roles, translating AI security concepts for customer and executive audiences through briefings, workshops, or advisory engagements.
• Industry certifications such as CISSP, OSCP, or AWS/Azure/GCP security certifications; emerging AI-security-specific credentials (e.g., AI red-teaming or AI/LLM security certifications) are especially valued.

Benefits

• Health (Medical & Prescription), Dental, and Vision Care
• Onsite Health Centers (MO & IL)
• Employee Assistance Program
• Wellness program
• Competitive Pay
• Profit Sharing
• 401k Plan with Company Matching
• Life and Disability Insurance
• Flexible Spending Accounts
• Tuition Reimbursement
• PTO & Holidays
• Parental Leave
• Medical Leave
• Military Leave
• Bereavement
• Day of Caring
• Family Planning Benefits
• Nursing Mothers Benefits
• Voluntary Legal
• Voluntary Supplemental Accident/Illness/Hospital
• Voluntary ID Theft
• Pet Insurance
• Employee Discount Program