Staff AI & Data Engineer
AUD 160K-200K (estimate) Senior-level Full Time
Tasks
- Architect agentic AI systems with RAG and multi agent patterns
- Define and evolve platform architecture for data and AI workloads
- Design scalable lakehouse event driven and real time data processing architectures
- Embed Responsible AI security privacy and data governance practices
- Ensure observability resilience validation and operational support for pipelines and models
- Establish AI application patterns guardrails and standards
- Implement end to end MLOps and DataOps with CI CD monitoring and orchestration
- Implement risk aware engineering controls and compliance requirements
- Improve data quality lineage observability and reliability
- Integrate LLM and generative AI into enterprise workflows
- Lead design and delivery of scalable AI and ML solutions
- Lead design and optimization of batch and streaming data pipelines
- Mentor engineers and raise engineering quality across teams
- Own Databricks Unity Catalog medallion architecture standards
- Standardize tooling infrastructure patterns and automation with Git Terraform Docker and Kubernetes
Perks/Benefits
Skills/Tech-stack
AI Engineering | Agentic AI | Azure | Azure Event | Azure Event Hubs | CI/CD | DBT | Data Engineering | Data Governance | Data Privacy | Data Processing | Data Security | DataOps | Databricks | Deep learning | Docker | Event Driven | Event Hubs | Event-driven architecture | Git | Infrastructure as Code | Kafka | Kubernetes | Lakehouse | Language Models | Large Language Models | Lifecycle Management | MLOps | Machine Learning | Medallion Architecture | Model Lifecycle | Model Lifecycle Management | Monitoring | Observability | Orchestration | Python | Real Time | Real-time Data | Real-time Data Processing | Responsible AI | Retrieval-Augmented Generation | SQL | Terraform | Testing | Unity Catalog | “as-code”
Education
N/A
Roles
AI Engineer | Data Engineer | Engineer | Staff AI Engineer | Staff Data Engineer
Regions
Countries
States
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