Staff Platform Engineer, AI Security

About the role

CommBank is looking for a Staff Platform Engineer, AI Security, to shape the platform capabilities that protect generative AI, large language model and agentic workloads. This is a hands-on technical leadership role combining platform engineering, cloud, security and artificial intelligence, working in Group Security, which covers cyber security, protective security, business resilience, fraud technology and cyber defence.

Key responsibilities

• Design and build shared platform capabilities that deliver AI security controls consistently, reliably and at enterprise scale.
• Build reusable services, APIs, libraries, templates and automation for policy enforcement, configuration management and telemetry.
• Design integration patterns for securing AI traffic, model interactions, APIs and agentic architectures.
• Establish engineering standards and guardrails using automated testing, infrastructure-as-code, configuration-as-code and modern continuous delivery.
• Design for resilience, scalability and maintainability, considering the latency, throughput and capacity impact of controls in AI request paths.
• Lead prototypes and proofs of concept, and establish observability through metrics, logs, traces, dashboards and alerting.
• Mentor engineers and influence technical decisions across security, cloud, platform and application teams.

Required profile

• Extensive experience in platform, software, cloud or site reliability engineering, with a track record of building shared platforms used by multiple teams.
• Demonstrated technical leadership, including mentoring engineers and influencing decisions across organisational boundaries.
• Experience integrating security controls into platforms or application request paths.
• Ability to evaluate emerging AI technologies through experimentation, prototyping and proof of concept.

Required skills

• Cloud-native engineering: containers, orchestration, infrastructure-as-code and automated delivery.
• Software engineering across services, APIs and integration patterns.
• Resilient, scalable, observable and highly automated production systems.
• Preferred: AI or ML platforms, AI gateways, model endpoints, agentic architectures, Kubernetes, proxies, service mesh, distributed tracing, policy-as-code.
• Preferred: Go, Python, Java, TypeScript or a comparable language.