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AI Security Engineering Manager

Engineering ManagerEngineering ManagerFull TimeRemoteLeadTeam 10,001+Since 1903H1B SponsorCompany SiteLinkedIn

Location

India

Posted

77 days ago

Salary

0

Seniority

Lead

Job Description

AI Security Engineering Manager

Ford Motor Company

• Design and build scalable AI security platform capabilities protecting AI models, AI pipelines, and AI applications. • Implement security across the AI lifecycle, including model governance, runtime protection, and secure AI deployment. • Integrate enterprise AI protection capabilities including Microsoft AI Security, Prisma AIRS, and Google Model Armor. • Implement AI endpoint protection capabilities, including KOI AI endpoint security, to protect AI workloads running on enterprise endpoints and developer environments. • Secure AI interactions across developer endpoints, APIs, and AI-enabled applications. • Implement controls to mitigate prompt injection, data leakage, model abuse, and adversarial AI threats. • Partner with Cybersecurity Team & Integrate AI security telemetry with enterprise detection platforms such as Google SecOps. • Support SOC to build detection capabilities for AI-specific threats and misuse patterns. • Secure AI workloads across Google Cloud (GCP), and Microsoft Azure. • Implement secure infrastructure using Terraform and Infrastructure-as-Code. • Design security controls for Kubernetes-based AI platforms, APIs, and microservices. • Develop automation and security tooling using Python, APIs, and modern full-stack development practices. • Lead and mentor a team of AI security engineers and platform engineers. • Partner with AI engineering, platform engineering, and cybersecurity teams to embed security into enterprise AI development.

Job Requirements

  • 12+ years of experience in cybersecurity, cloud security, or platform engineering.
  • 3+ years of experience securing AI/ML platforms or AI-driven applications.
  • 4+ years of hands-on software development experience, preferably in Python.
  • Strong expertise in:
  • AI / ML security
  • API and microservices security
  • Full-stack development
  • Hands-on experience with:
  • Kubernetes security
  • Terraform / Infrastructure-as-Code
  • Cloud platforms (GCP, AWS, Azure)
  • Preferred Certifications
  • CISSP – Certified Information Systems Security Professional
  • CCSP – Certified Cloud Security Professional
  • Google Professional Cloud Security Engineer
  • AWS Security Specialty
  • Microsoft Azure Security Engineer (AZ-500)
  • Certified Kubernetes Security Specialist (CKS)

Benefits

  • Health insurance
  • Retirement plans
  • Paid time off
  • Flexible work arrangements
  • Professional development
  • Bonuses
  • Stock options

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