Staff Software Engineer

Staff Software Engineer – Full Stack (AI Predictive Hedging team)

Do work that matters

At CommBank, we build digital banking services used by millions. The AI Predictive Hedging team designs and runs scalable, reliable platforms that power critical business capabilities and redefine customer experiences

See yourself in our team

As a Staff Software Engineer, you’ll play a hands‑on technical leadership role across the full SDLC—shaping architecture, building high‑quality software, and mentoring engineers. We’re AWS‑first, running our application stacks and data platforms entirely on AWS

What you’ll do

• Design, build, and operate secure, scalable front‑end, backend, and data solutions

• Lead end‑to‑end delivery on AWS: architecture, IaC, build, deploy, operate, and optimise

• Build Python‑based batch and large‑scale data pipelines (ETL/ELT) on AWS

• Develop event‑driven and streaming integrations for real‑time use cases

• Influence architecture across microservices, APIs, data flows, and cloud infrastructure

• Champion engineering excellence: code quality, testing, automation, and reliability

• Mentor engineers and uplift technical standards across the team

Skills & experience

Core (Java & Python required):

• Front‑end: React or Angular, TypeScript/JavaScript

• Backend: Java (Spring Boot) and Python microservices

• Data: Python data pipelines (e.g. PySpark/Beam), strong SQL

• Streaming: Kafka or AWS Kinesis; event‑driven patterns

• Architecture: Microservices, APIs, scalable and resilient systems

AWS experience:

• Compute & containers: ECS/EKS, Fargate, Lambda

• Data & analytics: S3, Glue/EMR, Step Functions

• Integration: API Gateway, SQS/SNS, Kinesis/MSK

• IaC & CI/CD: Terraform or CDK/CloudFormation, GitHub Actions

• Observability & security: CloudWatch, tracing, IAM, encryption

Nice to have:

• Experience deploying ML models into production (batch or real‑time)

• Understanding of MLOps concepts: model lifecycle, versioning, monitoring, retraining

• Exposure to AWS ML tooling (e.g. SageMaker or equivalent)

• Experience integrating ML outputs into data platforms or real‑time services

We’re interested in people who

• Deliver high‑quality software and data solutions at scale

• Influence technical decisions and collaborate across teams

• Care deeply about engineering craft, reliability, and simplicity

• Mentor others and foster a culture of continuous improvement

Working with us
We support flexibility in how and where work is done, with at least half your time each month connecting in our Sydney office. Flexible options include adjusted start/finish times, part-time, and job share. You’ll be supported to tackle new challenges and thrive in a team that values customer impact, craftsmanship, and continuous learning.

If you’re excited to build at scale on AWS across services and data, care deeply about quality, and want to make a meaningful impact for millions of customers, we’d love to hear from you.