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AI Security Engineer

Job in Cary, Wake County, North Carolina, 27518, USA
Listing for: MetLife
Full Time position
Listed on 2026-07-13
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Cybersecurity, Systems Engineer
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below

As part of Met Life’s Global Security team, you’ll work alongside world-class experts to protect Met Life, our customers and our colleagues. The team is responsible for managing cybersecurity, IT risks and vulnerabilities, physical security, and more. In this fast‑paced, mission‑driven environment, you’ll join outstanding teammates to expand your skills, collaborate across the organization and implement innovative approaches to safeguard Met Life when it matters most.

Ready to make an impact? Join us if you want to embrace the rapidly evolving environment and use transformative technology to integrate and build security into the foundation of key initiatives across Met Life.

The Opportunity

The Senior Engineer – AI Security Engineering will serve as a senior individual contributor focused on the design, build, deployment, and continuous improvement of security controls for AI systems across the enterprise. This is a hands‑on engineering role for a technically strong practitioner who can partner across security, cloud, platform, and application teams to secure AI use cases at scale.

Core Focus Areas
  • Engineer and operationalize security controls for AI systems, services, and supporting infrastructure
  • Accelerate safe adoption of AI capabilities across business and technology teams
  • Evaluate, pilot, and implement AI security tooling and control frameworks
  • Improve visibility, detection, and risk reduction for enterprise AI usage
  • Provide technical guidance and implementation patterns for secure AI deployment
Key Responsibilities
  • AI Security Engineering & Platform Controls
  • Engineer and operationalize controls for:
    • Prompt protection and filtering
    • Sensitive data protection in AI workflows
    • Secure model access and service integration
    • Policy enforcement for AI usage and governance requirements
  • Contribute to the design and implementation of reusable AI security capabilities across enterprise environments
  • Help define secure patterns for enterprise AI services, vendors, and internal use cases
  • AI Environment Hardening
  • Secure AI hosting environments, including:
    • Cloud-native platforms
    • Containerized and Kubernetes-based workloads
  • Integrate security controls into:
    • Application and deployment pipelines
    • AI/ML lifecycle workflows
    • Runtime environments
  • Validate configurations, reduce attack surface, and improve control effectiveness
  • Detection, Monitoring & Response
  • Improve technical visibility into:
    • AI system usage and behavior
    • Model misuse, anomalous activity, and data exposure risks
  • Partner with SOC and detection engineering teams to:
    • Develop detections and telemetry use cases
    • Improve monitoring coverage for AI platforms and workflows
    • Reduce manual effort through automation and enrichment
  • Engineering Execution & Innovation
  • Lead hands‑on engineering, prototyping, and implementation activities
  • Evaluate emerging AI security tools, patterns, and techniques through proof‑of‑concept work
  • Identify design and control gaps in AI, cloud‑native, and application environments
  • Develop practical solutions that improve security while supporting speed and usability
  • Cross‑Functional Collaboration
  • Partner with:
    • Cloud and platform engineering
    • Application development teams
    • AI/ML engineering teams
    • Security architecture, governance, and risk stakeholders
  • Translate security requirements into implementation guidance, engineering standards, and actionable technical patterns
  • Support adoption by providing practical recommendations and technical enablement
  • Technical Influence
  • Serve as a senior technical contributor and subject matter resource for AI security engineering
  • Help shape standards, guardrails, and repeatable patterns for secure AI deployment
  • Stay current with the evolving AI threat landscape, emerging architectures, and control capabilities
  • Share technical knowledge and mentor peers informally across the organization
Required Qualifications
  • 5+ years of experience in security engineering, cloud security, platform engineering, or a related technical discipline
  • Experience delivering enterprise‑scale security engineering solutions in complex environments
  • Demonstrated success in a senior individual contributor role requiring strong technical ownership and cross‑functional collaboration
Core…
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