AI Security Engineering Manager
Tasks
- Automate DevSecOps for AI pipelines
- Build AI threat detection capabilities
- Define AI security engineering roadmap and standards
- Design AI security platform capabilities
- Design Kubernetes security controls
- Develop Python security tooling and APIs
- Implement AI endpoint runtime security
- Implement AI lifecycle security
- Implement infrastructure as code with Terraform
- Integrate AI security platforms
- Integrate AI security telemetry with detection platforms
- Lead and mentor AI security engineers
- Mitigate prompt injection and data leakage
- Secure AI workloads on cloud platforms
Perks/Benefits
- N/A
Skills/Tech-stack
AI Security | AI/ML | AI/ML Security | API Security | AWS | Abuse protection | Adversarial AI | Cloud Security | Data Leakage Prevention | Data leakage | DevSecOps | Endpoint Security | Full Stack | Full-Stack Development | Google Cloud | Google Model Armor | Google SecOps | Google Security Command Center | Google Security Command Center Enterprise | Google security | Infrastructure as Code | KOI AI Endpoint Security | Kubernetes security | Leakage prevention | ML Security | Microservices Security | Microsoft AI | Microsoft AI Security | Microsoft Azure | Model Abuse Protection | Model Armor | Model abuse | Palo Alto | Palo Alto Prisma | Palo Alto Prisma AIRS | Prisma Airs) | Prompt injection | Prompt injection mitigation | Python | Stack development | Terraform | “as-code”
Education
N/A
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