Senior AI Security Engineer - Data & AI Platform

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 isolation to support robustness and prevent model theft
• Collaborate with Senior AI Security auditors and AI Engineers to ensure implementations pass governance consistently

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