# Principal Software Engineer, Group AI Enablement at Commonwealth Bank of Australia

Commonwealth Bank of Australia is hiring a Principal Software Engineer, Group AI Enablement. Level rates it Works on AI ●●●○; you can [apply on Commonwealth Bank of Australia](https://jobsbylevel.com/go/dcef4d3e-0eae-4596-8321-37066643708f?utm_medium=ai-agent).

AI Level 3, AI centrality 70 out of 100. Eveleigh, NSW - 1 Locomotive Street.

## Details

- Company: [Commonwealth Bank of Australia](https://jobsbylevel.com/companies/commonwealth-bank-of-australia)
- AI level: AI Level 3 (score 70 out of 100)
- Location: Eveleigh, NSW - 1 Locomotive Street
- Posted: November 10, 2026
- Apply: https://jobsbylevel.com/go/dcef4d3e-0eae-4596-8321-37066643708f?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=principal-software-engineer-group-ai-enablement-at-commonwealth-bank-of-australia-8ce3e3

## Prepare for this job

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## Description

Principal Software Engineer | Group AI Enablement *Sydney or Melbourne locations Shape the engineering strategy behind AI capabilities that transform how CommBank works. Lead complex engineering across agentic AI, RAG, cloud platforms and enterprise integrations. Build secure, reliable and reusable AI foundations that scale across the Group. Do work that matters Group AI Enablement sits within the Chief AI Office, part of Group Central Technology. Our mission is to help CommBank realise the value of AI by shaping and scaling enterprise capabilities that improve how our people work and the outcomes they deliver. As Principal Engineer, you’ll lead the technical strategy and architectural direction for Group AI Enablement, connecting our enterprise AI ambitions with the engineering foundations needed to deliver them. Your scope will span multiple teams, platforms and business functions. You’ll work with product leaders, Staff Engineers, technology teams and enterprise partners to establish a coherent technical direction, solve complex engineering challenges and create approaches that enable AI capabilities to scale across the Group. You’ll remain hands-on where your expertise has the greatest impact, testing emerging technologies, building reference implementations, validating architectural decisions and solving critical production problems. See yourself in our team You’ll join a team focused on moving AI from experimentation to useful, secure and reliable enterprise capability. In this role, you will: Define the long-term engineering strategy and architecture for enterprise AI capabilities, balancing immediate delivery with scalability, resilience and commercial value. 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. Engineer for trust by translating cyber security, privacy, risk and Responsible AI requirements into practical engineering controls. Remain hands-on through prototyping, software design and review, technical investigations and resolution of critical production challenges. Mentor senior technical practitioners and influence engineering decisions across organisational boundaries. We’re interested in hearing from people who: You’re an experienced engineering leader who combines strong architectural judgement with deep hands-on software engineering capability. You can move comfortably between strategic technical decisions and implementation detail, navigate ambiguity and bring multiple teams together around a clear engineering direction. Experience across several of the following will set you up for success: Leading complex engineering initiatives across multiple teams, platforms and stakeholders. Designing distributed, cloud-native systems and enterprise integration patterns, with strong AWS and/or Microsoft Azure experience. Building retrieval-augmented generation solutions using LlamaIndex, LangChain or comparable frameworks, including ingestion, retrieval, grounding, permissions and evaluation. Designing or building agentic systems involving tool use, orchestration, state management, human approval and failure recovery. Strong software engineering capability using Python, TypeScript, C# or comparable modern languages. DevSecOps, infrastructure as code, automated testing, CI/CD, observability and operational resilience. Evaluating AI systems across quality, safety, latency, reliability and cost. Working with product and business stakeholders to connect engineering decisions with measurable customer, employee or productivity outcomes.

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