About the job

Work at the forefront of responsible AI transformation

Shape enterprise AI governance and trust frameworks

Be part of a growing AI capability with real impact

Our people are customer obsessed. They prioritise the needs and satisfaction of the customer above all else.  Our mindset fosters innovation and creates strong, lasting customer relationships as we strive to be the most customer centric company in Australia and New Zealand

In the role of Senior Consultant Specialist, you will join the AI COE team that’s doubling down on customer obsession.

In this Senior Consultant Specialist role, you will:

• Build guardrails, validators, LLM judges, oversight modules, and deterministic execution wrappers into backend services.
• Develop evaluation pipelines for safety, robustness, behavioural testing, and policy compliance.
• Integrate safety checks into CI/CD workflows and enforce automated quality gates for agentic deployments.
• Implement and operate safety-critical components in AWS, ensuring scalability, security, and reliability.
• Maintain observability for agentic systems: logs, metrics, drift detection, alerts, and anomaly detection.
• Contribute to technical design documentation, patterns, and engineering standards for AI assurance.

We’re looking for the best and brightest to deliver the best for our customers. You’ll need:

• Proven experience in backend engineering, platform engineering, MLOps, or applied data science.
• Hands-on experience building APIs, microservices, or middleware within cloud environments.
• Exposure to LLM or agentic systems—e.g, retrieval, prompt engineering, tool orchestration, agent runtime integration.
• Experience implementing risk controls, safety checks, automated quality gates, or security patterns.
• Familiarity with evaluation frameworks, red-teaming methodologies, or ML testing.
• Experience participating in incident investigations or remediation for production systems beneficial.

A diverse and inclusive workplace works better for everyone

We know that our people make us who we are. That’s why we have built a culture of equity and respect - where everyone feels valued and appreciated for being their authentic selves. In partnership with our multiple Employee Resource Groups (ERGs), we continue to foster an inclusive environment, where all NAB colleagues’ unique backgrounds and identities are understood, respected and celebrated. We are committed to providing an environment where you can work your way.

• Build guardrails, validators, LLM judges, oversight modules, and deterministic execution wrappers into backend services.
• Develop evaluation pipelines for safety, robustness, behavioural testing, and policy compliance.
• Integrate safety checks into CI/CD workflows and enforce automated quality gates for agentic deployments.
• Implement and operate safety-critical components in AWS, ensuring scalability, security, and reliability.
• Maintain observability for agentic systems: logs, metrics, drift detection, alerts, and anomaly detection.
• Contribute to technical design documentation, patterns, and engineering standards for AI assurance.

• Proven experience in backend engineering, platform engineering, MLOps, or applied data science.
• Hands-on experience building APIs, microservices, or middleware within cloud environments.
• Exposure to LLM or agentic systems—e.g, retrieval, prompt engineering, tool orchestration, agent runtime integration.
• Experience implementing risk controls, safety checks, automated quality gates, or security patterns.
• Familiarity with evaluation frameworks, red-teaming methodologies, or ML testing.
• Experience participating in incident investigations or remediation for production systems beneficial.

• Proven experience in backend engineering, platform engineering, MLOps, or applied data science.
• Hands-on experience building APIs, microservices, or middleware within cloud environments.
• Exposure to LLM or agentic systems—e.g, retrieval, prompt engineering, tool orchestration, agent runtime integration.
• Experience implementing risk controls, safety checks, automated quality gates, or security patterns.
• Familiarity with evaluation frameworks, red-teaming methodologies, or ML testing.
• Experience participating in incident investigations or remediation for production systems beneficial.