Lead the technical strategy and architectural direction for Group AI Enablement, connecting enterprise AI ambitions with the engineering foundations needed to deliver them.
Locations (2)
Sydney, New South Wales, Australia
Melbourne, Victoria, Australia
Responsibilities
Define the long-term engineering strategy and architecture for enterprise AI capabilities.
Shape how AI models, agents, knowledge sources and business systems integrate, establishing patterns that enable security, interoperability and reuse.
Lead complex engineering initiatives from discovery and experimentation through to production.
Build reusable services, reference implementations and engineering patterns covering identity, permissions, observability and operational ownership.
Establish rigorous approaches to evaluating RAG and agentic systems using representative business tasks and measurable success criteria.
Lead the design and governance of scalable, secure, and resilient payment solutions across Account-to-Account (A2A) payments covering Domestic (NPP, Direct Entry), International, and RTGS ecosystems.
Responsibilities
Lead end-to-end solution architecture across Payments initiatives
Define and evolve Payments domain architecture aligned to service domain models and API standards
Provide strategic architecture guidance across multiple crews ensuring consistent adoption of standards
Drive platform modernisation through API enablement, domain decoupling, and event-driven architecture
Design solutions with high availability, resilience, and regulatory compliance
Requirements
Bachelor’s degree or Master’s degree in Engineering in Computer Science/Information Technology
Nice to have: Australian domestic payments experience
Nice to have: International payments and correspondent banking
Lead the design and delivery of scalable, high-performance real-time payment solutions across modern cloud-native platforms, focusing on Australia’s payments landscape.
Responsibilities
Provide technical leadership and engineering direction across complex software initiatives.
Lead system design and make pragmatic architectural decisions for secure, scalable and high-performance distributed applications.
Design and evolve APIs and microservices using Node.js and TypeScript, and Java and Spring Boot where it fits.
Build cloud-native solutions using AWS, containerisation and Infrastructure as Code.
Apply event-driven architecture and messaging technologies such as Kafka to solve complex integration and distributed-system challenges.
Requirements
Nice to have: payments experience
Nice to have: real-time processing
Nice to have: high-throughput transaction processing
Principal Software Engineer leading technical strategy and architecture across full‑stack platforms and AI‑enabled capabilities.
Responsibilities
Set and drive technical strategy, target architecture and engineering direction across a portfolio of full‑stack capabilities spanning modern web applications, APIs, services, data and AWS cloud platforms.
Provide authoritative technical leadership across .NET/C#, Java/JVM or Node.js/TypeScript ecosystems and modern TypeScript frontends.
Define architecture for secure, resilient distributed systems at scale, establishing domain/service boundaries, event‑driven and asynchronous patterns, consistency models, idempotency, fault tolerance and evolutionary architecture principles.
Shape workflow architecture using Temporal and durable orchestration patterns, establishing approaches for long‑running processes, retries, compensation, human‑in‑the‑loop steps, state management, business rules, versioning and auditability.
Lead complex modernisation and simplification across legacy estates through decomposition, API enablement, event‑driven integration and cloud migration.
Requirements
Bachelor of Engineering, BTech or equivalent qualification
A technical leadership role focused on designing and modernizing large-scale applications using Java, Spring Boot, microservices, and Pega on cloud-native platforms.
Compensation
Bangalore - Manyata Tech Park Road
Responsibilities
Lead the architecture, design and delivery of Java, Spring Boot, APIs, microservices and Pega solutions
Drive application modernisation and cloud-native engineering, including legacy decomposition, API enablement, AWS migration, containers/Kubernetes/ECS, infrastructure as code, CI/CD and DevSecOps
Define architectural boundaries and integration patterns across Pega, Java services, enterprise platforms and external systems
Establish and champion strong engineering practices covering clean code, API design, automated testing, security, observability, performance, production readiness, code/design reviews and troubleshooting
Provide technical leadership and mentoring across engineering teams, collaborate with product and architecture stakeholders, and enable appropriate adoption of Generative AI and Agentic AI capabilities
Requirements
Bachelor’s degree or Master’s degree in engineering in Computer Science/Information Technology
Lead the design, development and implementation of Responsible AI capabilities across the Commonwealth Bank Group, providing technical leadership and guiding architecture, risk controls, and delivery practices for Generative and Agentic AI systems.
Responsibilities
Provide technical leadership in the design, development and implementation of world‑class evaluation and assurance capabilities for Generative and Agentic AI
Partner with engineering, data science, risk and policy teams in designing and delivering Responsible AI capabilities
Partner with risk and policy teams in building and operating formal risk controls
Establish executive risk reporting for senior leadership
Apply statistical methods and structured problem solving to complex Responsible AI challenges
Requirements
Tertiary qualification in Data Science, Statistics, Computer Science, Engineering, Mathematics or a related discipline
Lead a data science team focused on Responsible AI across the Commonwealth Bank Group, shaping technical direction and delivering capabilities for Generative and Agentic AI.
Responsibilities
Lead and develop a team of data scientists through coaching, knowledge sharing, technical guidance and collaboration
Lead the design, development and implementation of world-class evaluation and assurance capabilities for Generative and Agentic AI
Partner with engineering, data science, risk and policy teams in designing and delivering Responsible AI capabilities
Partner with risk and policy teams in building and operating formal risk controls
Establish executive risk reporting
Requirements
Tertiary qualification in Data Science, Statistics, Computer Science, Engineering, Mathematics or a related discipline