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About the Role

We are seeking a Chief Engineer to lead the technical strategy, architecture, and engineering standards across Operations technology platforms at CBA. This role is responsible for ensuring our systems are resilient, secure, compliant, and scalable, while supporting critical business capabilities servicing 3000+ internal users. You will act as the senior-most technical authority across Operation Tech domain, driving modernisation of legacy platforms, uplifting engineering practices, and ensuring alignment with CBA’s enterprise architecture, risk frameworks, and regulatory obligations.

Responsibilities

• Lead modernisation initiatives, Engineer enterprise-wide platform adoption (cloud adoption, AI implementation, decommissioning legacy systems)
• Ensure alignment with CBA enterprise architecture, data strategy, and platform standards
• Drive AI first mindset and API-first, event-driven, and modular architecture patterns
• Establish best practices for high availability, disaster recovery, and operational resilience
• Drive improvements in system reliability, observability, and incident management
• Champion secure engineering practices aligned with CBA cybersecurity standards
• Ensure strong SDLC governance, including CI/CD, automated testing, and release controls
• Ensure the accuracy, consistency, lineage, and trustworthiness of enterprise data, enabling secure, high-quality data foundations across platforms and business domains.
• Design and govern AI-ready data architectures, including data lineage, reconciliation, observability, metadata, and controls across upstream and downstream systems.
• Establish responsible AI guardrails by implementing enterprise AI governance, model evaluation, prompt and agent governance, knowledge management, and human oversight to ensure safe, compliant, and explainable AI adoption.
• Build reusable AI and data platform capabilities, including enterprise knowledge layers, vector search, RAG, AI skills, and operational data products that enable scalable agentic solutions and intelligent automation.
• Integrate enterprise data, AI services, and risk, compliance, analytics, and reporting platforms to deliver trusted, governed, and reusable capabilities across the organisation.
• Champion AI engineering best practices, including model lifecycle management, evaluation frameworks, observability, security, and continuous improvement of AI-powered systems.
• Provide technical leadership across multiple engineering teams and domains
• Mentor principal engineers and engineering leaders
• Build a culture of accountability, engineering excellence, and continuous improvement
• Influence hiring, capability uplift, and workforce strategy
• Partner with senior leaders across Operation, Financial crime Technology
• Translate complex technical concepts into business and regulatory impact
• Support executive and board-level discussions where required (e.g. risk, resilience, incidents)

Requirements

• 15+ years of engineering experience, with significant time in enterprise-scale or banking environments
• Proven experience leading complex technology platforms
• Deep expertise in distributed systems, data platforms, and cloud (AWS/Azure/GCP)
• Experience working within regulated environments (APRA, Basel frameworks, etc.)
• Demonstrated ability to lead large-scale transformation and modernisation programs
• Experience with Agentic solutions, technology modernization, regulatory reporting.
• Background in Data and microservice architecture, enterprise data platforms
• Experience in platform engineering or core banking transformation
• Strong technical depth with enterprise-scale thinking
• Risk-aware decision maker with strong governance mindset
• Influential leader comfortable operating at executive level
• Pragmatic approach to balancing legacy constraints with modernisation goals

Skills

• Cloud adoption
• AI implementation
• Legacy system simplification
• Platform architecture
• Data governance
• AI integration
• Secure engineering practices
• Operational resilience
• API-first architecture
• Event-driven architecture
• Modular architecture
• High availability
• Disaster recovery
• System reliability
• Observability
• Incident management
• Cybersecurity
• SDLC governance
• CI/CD
• Automated testing
• Release controls
• Data lineage
• Data trustworthiness
• AI-ready data architectures
• Metadata
• Responsible AI
• AI governance
• Model evaluation
• Prompt governance
• Agent governance
• Knowledge management
• Human oversight
• Vector search
• RAG
• AI skills
• Agentic solutions
• Intelligent automation
• Risk management
• Compliance
• Analytics
• Reporting platforms
• Model lifecycle management
• AI engineering best practices
• Microservice architecture
• Enterprise data platforms
• Platform engineering
• Core banking transformation

Experience Level

• 15+ years of engineering experience

About the Company

• Commonwealth Bank Group (including Bankwest, x15ventures)

Equal Opportunity

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