Own the working relationship with CSG on data residency, PII handling, access governance, and model security controls
Translate policy into guardrails the delivery team and citizen developers can act on
Build and maintain security tooling, guardrail enforcement, and policy-as-code integrations across Enterprise AI platforms
Reduce manual review through automation where possible
Develop reusable security components and patterns that delivery teams and citizen developers can drop into Agent builds—making the secure path the easy path
Instrument AI platforms to detect anomalous behavior, access patterns, and policy violations
Build the detection layer, not just consume it

1 –2 years hands-on experience applying security and compliance controls to AI or ML systems
Familiarity with LLM-specific risks: prompt injection, data leakage, model access control, output filtering
Experienced defining architecture standards or technical guardrails
Familiarity with data residency requirements, PII handling, and access governance in enterprise environments
Ability to translate security requirements into developer-facing guidance
Demonstrated ability to build and implement solutions directly, not just document or advise

AI SecOps Engineer

Key skills