Top AI Jobs in Melbourne

Lead and grow an engineering team building AI-powered internal security tooling and automation. Drive execution from planning to delivery, build infrastructure (Kubernetes, serverless, ETL), support incident response with threat-hunting tools, and partner with product teams to reduce risk through automation and security services. Mentor engineers and identify opportunities for automation and tooling.

Lead development of internal AI-driven security tools and automation, support incident response with threat-hunting and remediation tooling, maintain Kubernetes/serverless infrastructure and large-scale log/ETL pipelines, identify automation opportunities with engineering teams, drive security outcomes (patching, gateways), and mentor junior engineers.

Lead design and build of internal AI tooling and automation to improve security operations. Develop ad-hoc incident response and threat-hunting tools, maintain Kubernetes, serverless, and ETL/data pipelines, and partner with product teams to automate patching and risk-mitigation services. Own large-scale log pipelines, mentor junior engineers, and deliver high-quality projects autonomously.

Lead discovery, design, and delivery of Agentic AI POCs on the ServiceNow platform in 3-4 week sprints. Scope and run consultative workshops, configure AI agents, integrate enterprise data sources, build reusable prompt libraries and agent templates, support sales technical positioning, and orchestrate engineers to produce production-ready prototypes and handoffs.

Lead field-facing AI security strategy for enterprise customers: design secure LLM/RAG architectures, deliver demos and POVs, advise on data protection and Zero Trust, and scale enablement content across sales and product teams.

Lead design and implementation of AI research and production infrastructure. Mentor junior engineers, and collaborate to enhance data usability, solving complex technical challenges.

The Solution Sales Executive will drive sales of FICO's platform in financial services, engaging with clients, managing relationships, and collaborating with internal teams to deliver solutions.

Design and implement large-scale, production-grade distributed systems to power generative AI features. Own architecture, operational reliability, and technical debt. Collaborate with applied scientists to productionize ML/LLM models, mentor engineers, and improve data usability and engineering standards.

Lead design and implementation of large-scale distributed production systems powering generative AI features. Own architecture, mentor engineers, manage technical debt, operationalize ML/LLM models, and collaborate with scientists to productionize research using Python, SQL, Spark/Dask, AWS, and Kubernetes.

Design, build, and operate an internal AI skills marketplace and distribution platform. Own end-to-end delivery from experimentation to production, create runbooks, monitoring, rollback plans, and provide guidance on authoring agent skills while collaborating with vendors and engineering teams.

The Clinical Development Analyst specializes in developing and managing Computer-Assisted Coding for healthcare, ensuring alignment with coding standards and compliance, and providing clinical expertise in coding development.

Lead engineering teams to improve Azure Storage service quality, resiliency, chaos engineering, and validation infrastructure. Integrate AI tools and Responsible AI across the SDLC, coordinate cross-team plans, resolve complex incidents, and ensure scalable performance and best practices.

Provide commercial legal support for ANZ sales, professional services and alliances: draft, review and negotiate contracts; support contracting/order processes; partner with privacy, security and compliance; handle contract disputes, compliance with AU/NZ law, training, and cross-regional projects.

The Content Solutions Engineer will act as a subject matter expert in AI and Machine Translation, providing pre-sales support, technical consulting, and collaborating on solution architecture to help clients optimize globalization processes.

Join CommBank's Data Science & AI Talent Community to build AI solutions improving customer outcomes while fostering responsible and ethical use of AI. Positions available range from Data Scientist to Principal Data Scientist, emphasizing collaboration and innovation in a flexible work environment.

The Reserve Engineer maintains and services robotic hardware, responds to failures at client sites, and ensures customer satisfaction. Responsibilities include learning hardware, communicating repairs, and assisting with deployment projects.

Lead and deliver detailed design for large water and wastewater treatment plants, prepare technical reports, drawings and specifications, manage client relationships, support bids and proposals, mentor staff, and ensure safe, constructable, and commercially viable design solutions.

As a Senior Engineer, you'll develop AI workflows, lead delivery of AI agents, and integrate systems while collaborating with business teams to automate processes.

The Business Development Manager will onboard new sellers, build relationships, conduct market research, negotiate contracts, and collaborate with internal teams.

Promote Lilly's cardiometabolic health products, build relationships with healthcare professionals, travel regionally, maintain customer satisfaction, and comply with standards.

Lead design and build of ML systems (especially LLMs/foundation models) to deliver AI features like document understanding, forecasting, and conversational interfaces. Deploy, scale, and optimise models on AWS (SageMaker/Bedrock/S3), implement MLOps (CI/CD, versioning, monitoring, containerisation) and own projects end-to-end while collaborating with product and engineering teams.

Drive development of MYOB's SaaS platform as a senior full-stack developer. Collaborate on building web services and 3rd-party integrations, deploy cloud solutions (Azure/AWS) with scalability and resilience in mind, apply TDD, DevOps, CI/CD, clean code and event-driven architecture, and adapt to evolving technical directions.

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).

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 and implement a multi-agent AI orchestration framework for proactive GTM workflows: build signal pipelines, reasoning and scoring components, content generation, production integrations (Salesforce, Teams), governed AI foundations, observability, and developer enablement.