Job Description

The Secure AI Engineer is responsible for the delivery of consulting and engineering services across Secure AI, AI-enabled applications, and up-to-date cloud environments.

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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.

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What You'll Do

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



reference patterns, and internal capability uplift across the Secure AI team
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- Collaborate across CyberCX practices where engagements span cloud, identity, application security, data, or governance domains
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What You'll Bring

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