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CyberCX

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Secure AI Engineer (Specialist)

🗓️ Posted 2026-08-17 Canberra, Australian Capital Territory, Australia Full-time Hybrid ICT

Company shared salary

NA

Market rate

A$12,000–A$20,000/mo (A$144,000–A$240,000/yr)

Based on similar roles (title + domain + location).

About the Role

The Secure AI Engineer is responsible for the delivery of consulting and engineering services across Secure AI, AI-enabled applications, and modern cloud environments. Working closely with clients, teammates, and other practices you will contribute to a range of engagements across design review, implementation support, control uplift, and technical assessment, helping organisations adopt AI in a secure and responsible way.

Responsibilities

  • ● Support the delivery of secure AI and application security engagements for enterprise and government clients
  • ● Contribute to reviews of AI-enabled applications, workflows, platforms, and integrations
  • ● Assist in identifying risks across models, prompts, data flows, APIs, cloud services, and supporting systems
  • ● Help define practical recommendations to improve security, governance, and delivery controls
  • ● Build or configure technical controls, patterns, and supporting artefacts for secure AI implementations
  • ● Produce clear, high-quality client deliverables, including technical products, findings, recommendations, implementation guidance, and supporting documentation
  • ● Work with client stakeholders to understand their environment, priorities, and constraints
  • ● Contribute to reusable templates, reference patterns, and internal capability uplift across the Secure AI team
  • ● Collaborate across CyberCX practices where engagements span cloud, identity, application security, data, or governance domains

Requirements

  • ● Experience in software engineering, ML engineering, data science, cloud engineering, security engineering, or technical consulting
  • ● Experience building, reviewing, or supporting modern applications or cloud-based systems
  • ● Familiarity with secure development practices and common security concepts across AI, applications, infrastructure, and integrations
  • ● Ability to investigate technical issues, structure findings, and communicate clearly
  • ● Exposure to AI, ML, Generative AI, Agentic AI, or AI-assisted development use cases
  • ● Experience with AWS, Azure, or Google Cloud
  • ● Familiarity with application security review, threat modelling, IAM, API security, or workload security
  • ● Exposure to CI/CD, infrastructure as code, containerised workloads, or Kubernetes
  • ● Awareness of common security or risk frameworks such as NIST, ISO 27001, CIS, MAESTRO, or similar