Director of Software Engineering at Acuity leading AI - enabled digital commerce platform development and transforming user experience with modern architecture.
About the role
- Principal Software Engineer at CommBank shaping future banking through innovative engineering solutions. Guiding teams in complex challenges and ensuring scalable, reliable deliveries in Business Banking.
Responsibilities
- Champion cutting-edge solutions and drive real-world impact
- Guide the team through complex challenges ensuring scalability, security and reliability in delivery
- Collaborate within the Banker Assisted Lending crew in Business Banking to create differentiated banker experiences
Requirements
- Lead the decomposition of monoliths and build scalable microservices and event-driven applications
- Solve complex technical challenges from design to production
- Define architectural standards and tackle deep architecture issues
- Address tech debt with a pragmatic, commercially focused approach
- Translate requirements into solid engineering deliverables and delegate effectively
- Deliver reusable solutions used across teams and products
- Contribute directly to code delivery, lead reviews, and fix complex bugs
- Mentor junior engineers, hire top talent, and support career development
- Influence cross-functional teams and align technical decisions with business goals
- Experience in AI/ML Engineering to accelerate product development
- Leading large-scale, complex engineering initiatives
- Proficiency in languages: C#, .Net, Go, Java
- Experience with cloud: AWS, Serverless, Containers, VM Hosting
- Knowledge of databases: Aurora, RDS, Redis, ElastiCache, Oracle
- Familiarity with eventing: SQS, SNS, EventBridge, Kafka (MKS)
- Proficient in engineering tools: GitHub, GitHub Actions, Terraform Enterprise, Artifactory, AKKA, SST
- Understanding of observability tools: OpenTelemetry, Prometheus, Grafana, Observe, CloudWatch
- Knowledge of security tools: Vault, AWS Secrets Manager, Certificate Manager, Parameter Store
- Experience with testing methodologies: TDD, BDD, Automation Frameworks
- System design experience: Data-intensive apps, API/microservices/event-driven/serverless architecture
- Familiarity with deployment & SRE methodologies
- Side projects or commercial experience with AI tools like Anthropic Claude, Llama, LiteLLM, etc.
- Preferred certifications: AWS Solutions Architect / DevOps Engineer Professional, AWS AI Practitioner / Machine Learning Specialty, Certified Kubernetes Administrator (CKA) / Developer (CKD)
Benefits
- Flexible working options including changing start and finish times
- Part-time arrangements
- Job sharing
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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