Security Engineer - AI Security Enablement

Position Description: Security Engineer (AI Specialist)

Role Overview

• Role Type: Contract (6 months)
• Location: Melbourne (Hybrid)
• Project: Cyber Resilience - AI Security Enablement

Role Purpose

Working closely with Cyber Security, Digital, Data, and AI delivery teams, this role is responsible for implementing technical security controls that support the safe adoption of AI tools and agents across the enterprise. The successful candidate will provide dedicated security engineering capacity to operationalize the AI security control register, close identified control gaps, and ensure AI guardrails are implemented, embedded, and verified.

Key Responsibilities

• AI Security Control Implementation: Drive the AI security control register backlog in priority order, taking defined guardrails through to fully implemented, embedded, and verified controls.
• Foundational AI Security Engineering: Deliver technical security engineering for safe AI adoption, both ahead of deployment and retrospectively.
• Risk Assessment: Assess new and emerging AI use cases, agents, and related technologies for security risk, defining the necessary controls to enable them safely.
• Cross-Domain Security Controls: Design, implement, and maintain security controls across data, identity, endpoint, cloud, and application security domains as they relate to AI tools and agents.
• Policy & Configuration: Build, update, and implement technical security policies and configurations for AI tools, agents, data access, and integrations.
• Secure Development: Apply secure-by-design and DevSecOps principles to AI and agent-based solutions.
• Monitoring & Stewardship: Monitor the environment for emerging AI security risks and control gaps, while maintaining the active AI security control register.
• Reporting: Track and report implementation progress, blockers, and residual risks to senior cybersecurity management.

Required Skills & Experience

• Broad experience as a Security Engineer within an enterprise environment.
• Proven track record designing, implementing, and validating technical security controls across identity, data protection, endpoint, cloud, and application security.
• Strong understanding of secure-by-design and DevSecOps principles.
• Working knowledge of AI-specific security risks (e.g., agents, data exposure, excessive permissions, prompt injection, third-party AI services, and shadow AI).
• Ability to translate complex risk requirements into practical, implementable technical controls.
• Self-directed and capable of delivering independently against a prioritized backlog.