Lead AI Engineer

Reserve Bank of Australia

Sydney

1 week ago

Sydney

1 week ago

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Lead AI Engineer

Lead AI Engineer role at the Reserve Bank of Australia's Innovation Lab, focusing on designing and delivering enterprise-grade AI solutions. Requires hands-on experience with Azure AI, Python, and LLMs. Fixed-term contract until Aug 2027, hybrid work in Sydney.

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Hybrid

Contract

Lead

Python

Azure AI

Salary

Not specified

Work Location

Sydney, New South Wales, Australia, AU

Work Model

Hybrid

Employment Type

Contract

Experience Level

Not Applicable

Contract Length

38 months

Core Qualifications

Technical (Must-have)

PythonAzure AILLMsAI evaluation techniquesCI/CD pipelinesModelOpsMS AI FoundryCloudera AIcloud-native engineeringretrieval patterns

Soft Skills

collaborationmentoringleadershipcommunicationproblem solving

Preferred Qualifications

Technical (Nice-to-have)

C#R

Key Responsibilities

•Lead the design, development, and delivery of AI-powered applications and agents using MS AI Foundry, Cloudera AI and other approved platforms
•Take ownership of AI solution architecture, guiding prototypes through to reliable, enterprise-grade deployments
•Build and review production-quality code, with a strong emphasis on Python and cloud-native engineering practices
•Design and implement LLM-powered workflows, including retrieval patterns, orchestration, and evaluation
•Establish and uphold engineering best practices, including testing, validation, monitoring, and documentation
•Collaborate closely with product owners and cross-functional teams to refine requirements and define delivery outcomes
•Ensure AI solutions align with internal governance, risk, and responsible AI standards

Lead AI EngineerInnovation LabAzure AIPythonLLMFixed-term contractHybridSydneyFinancial servicesEnterprise AI

Key Responsibilities

•Lead the design, development, and delivery of AI-powered applications and agents using MS AI Foundry, Cloudera AI and other approved platforms

•Take ownership of AI solution architecture, guiding prototypes through to reliable, enterprise-grade deployments

•Build and review production-quality code, with a strong emphasis on Python and cloud-native engineering practices

•Design and implement LLM-powered workflows, including retrieval patterns, orchestration, and evaluation

•Establish and uphold engineering best practices, including testing, validation, monitoring, and documentation

•Collaborate closely with product owners and cross-functional teams to refine requirements and define delivery outcomes

•Ensure AI solutions align with internal governance, risk, and responsible AI standards