Principal AI Security Engineer, AI Native Platform
Tasks
- Architect identity and trust model for non human agents
- Define prompt injection defense and adversarial input handling
- Design access controls and data boundary enforcement for AI end user platform
- Establish security observability and response framework
- Implement model provenance practices and dependency controls
- Own security strategy for frontier model access and MCP governance
- Partner with privacy legal and data teams to secure data pipelines
- Set access control and data governance for shared knowledge layer
Perks/Benefits
Skills/Tech-stack
ABAC | Access Control | Access Management | Adversarial Machine Learning | Agent Authentication | Agent Orchestration | Application Security | Cloud Security | Data Governance | Detection engineering | IAM | Identity and Access Management | Identity and access | Injection Defense | LLM | Least Privilege | Machine Learning | Model provenance | Multi-Agent | Multi-agent orchestration | OAuth | Prompt injection | Prompt injection defense | RAG | RBAC | Retrieval-Augmented Generation | Secrets management | Security observability | Service Identity | Telemetry
Education
N/A
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