Top Tech Jobs & Startup Jobs in Melbourne

Lead and build end-to-end AI systems focused on LLMs and foundation models for small business features (document understanding, forecasting, conversational interfaces). Design, deploy, scale, and monitor ML models on AWS, establish MLOps best practices, optimize for safety and reliability, and mentor a small team while collaborating with product and engineering stakeholders.

Design, build, and maintain scalable, observable data pipelines and metadata frameworks to support analytics, AI/ML, and BI. Collaborate with engineers, data scientists, and analysts to improve data quality, governance, and delivery efficiency while driving best practices and MLOps integration.

Collaborate on design, build, test, deploy and support web-service based business software. Ensure quality via TDD, CI/CD, and design patterns; contribute to architecture, documentation, production support, and agile delivery.

Design, build and maintain API platform capabilities and developer portals. Develop and support REST and GraphQL APIs, implement authentication/authorization (OAuth2/OIDC/JWT/RBAC), build cloud-native services on Azure/GCP, improve reliability, performance, observability, CI/CD, and maintain documentation and code quality through cross-team collaboration.

Lead front-end delivery for SaaS products: define architecture and design systems, implement accessible, performant, and secure React/TypeScript UIs, embed testing and observability, mentor engineers, collaborate with Product and Design, and improve platform/pipeline for developer experience and reliability.

Lead enterprise change by developing and executing change strategies, stakeholder engagement, training, communications, and adoption plans. Drive readiness and measure success for large-scale transformation across people, process, and systems, partnering with leaders and project teams to ensure timely delivery and sustained behavioral change.

Lead a small AI engineering team to design, build and productionise ML systems focused on LLMs and foundation models. Develop AI features (document understanding, forecasting, conversational interfaces), implement MLOps (CI/CD, model versioning, monitoring), and deploy scalable, safe solutions on AWS (SageMaker, Bedrock, S3).