Описание
We are seeking a Senior AI Security Engineer to join the AI Foundation team and secure Enterprise AI and Scientific AI workloads across Azure and GCP platforms. This is an implementation-focused role where you will translate AI Security Framework controls into working platform configurations, engineering security as code through Terraform, GitOps CI/CD security gates, and policy-as-code that continuously attests to compliance. You will collaborate closely with Senior AI Security auditors and AI Engineers in a high-talent-density domain, ensuring implementations consistently pass governance requirements.
Responsibilities
Translate AI Security control descriptions into working platform configurations and defensible implementations Engineer security controls as code using Terraform, GitOps CI/CD pipelines, and policy-as-code frameworks Produce machine-verifiable evidence that proves adherence to control descriptions Implement Kubernetes GPU node pool segmentation, VNet/VPC isolation, and private endpoints across Azure and GCP Configure RBAC/ABAC least-privilege access, managed/workload identity, and risk-based access controls Build a hardened API integration layer and centralized gateway with tool-level access controls Deploy LLM guardrails for prompt/response injection, content filtering, kill-switches, and inference rate limits Set up observability pipelines for anomaly and drift detection, restricted-access logs, and end-to-end traceability Maintain training-data and model is
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