Top AI Jobs in Melbourne

As a Senior AI Engineer, you will develop and implement AI capabilities to enhance business processes and customer experiences, collaborating with teams to deliver scalable solutions.

As a Senior Applied AI Solution Engineer, you'll develop AI applications, consult with clients, lead projects, ensure ethical practices, and maintain AI solutions.

Design, build, and deploy AI applications using large language models. Involve client consultation, technical leadership, and quality assurance while ensuring ethical AI practices.

Lead engineering for Data & AI within Financial Services, shaping strategy, building scalable data platforms, ensuring operational excellence, governance and responsible AI adoption. Partner with Product and Architecture, hire and grow leaders, coordinate multi-team delivery and support cross-functional programs.

As a Senior Backend Engineer at Canva AI, you'll drive backend architecture, implement critical code, mentor engineers, and collaborate with teams to enhance the platform's scalability and integration capabilities.

Lead design, development, testing, and App Store submission of production-scale iOS features in Swift. Collaborate cross-functionally, enforce code quality via reviews and refactoring, maintain technical documentation, and adopt AI-assisted tooling to improve productivity across large, user-facing modules.

Design, build, and deploy scalable Generative AI and LLM production applications on GCP. Implement RAG architectures with vector databases, develop high-throughput APIs and microservices, collaborate with cross-functional teams, and apply prompt engineering, model optimization, and performance evaluation to ensure reliable AI solutions.

Lead design and delivery of enterprise-scale generative AI and multi-agent systems. Define reference architectures, RAG and vector knowledge layers, integration fabrics, observability, governance, and Responsible AI frameworks. Assess readiness, build roadmaps, coordinate cross-functional teams, and mentor engineering talent.

Lead design, build, and deploy production-grade Generative AI solutions. Architect and optimise RAG pipelines and vector DBs, integrate AI via secure APIs/microservices, manage prompt lifecycle, implement MLOps/versioning/monitoring, and mentor engineering teams.

Design, build, deploy and operate cloud-native, AI-enabled employee experiences using Python, AWS, Node.js and React. Contribute to architecture, platform components, CI/CD, DevSecOps, observability and AI-agent features while improving security, scalability and engineering quality.

Lead presales enterprise architecture for Data/AI and Applications, designing integrated multi-tower solutions (data platforms, GenAI, MLOps, application modernization, cloud, integration, AIOps). Drive account planning, C-suite workshops, bid leadership, value cases, demos, portfolios, and in-contract innovation while coaching teams and ensuring delivery and commercial alignment.

Lead design and delivery of AI-driven solutions from prototyping to production. Work with business leaders to identify opportunities, build prototypes, design scalable cloud-native architectures, implement APIs, CI/CD and deploy observable, secure AI systems. Mentor engineers and establish reusable AI patterns and best practices.

The Principal Technology Product Owner will lead cross-functional teams to develop Generative AI solutions, focusing on safety, customer needs, and governance while managing the product roadmap and stakeholder engagement.

Work lawyer-to-lawyer with senior legal stakeholders to drive adoption of LexisNexis Protege, translating workflow priorities into AI-enabled solutions, delivering demonstrations, supporting pre- and post-sales pursuits, capturing customer insights in CRM, and partnering with Relationship Managers to grow engagement and create new business opportunities.

Support maintenance and improvement of regulatory compliance content: perform legal research, draft and edit content, update formatting and metadata, conduct quality reviews, manage documentation and workflows, and assist content managers with day-to-day operational tasks across jurisdictions.

Validate and improve AI-generated legal and regulatory compliance outputs through legal research, testing, identifying gaps and edge cases, and providing structured feedback to product, engineering and data science teams. Support prompt design, evaluation frameworks, training data, taxonomy and metadata, and work across Australian, UK and global regulatory environments to enhance AI accuracy and customer outcomes.

Lead CX and AI strategy engagements: assess current-state, define future operating models, recommend CCaaS/CRM/AI platforms and architectures (MCP, A2A, APIs), design AI-enabled workflows, advise executives, and drive large-scale transformation with measurable business cases.

Provide strategic and people leadership for the Data Science & AI Discipline, advancing research, teaching and industry engagement; shape discipline strategy, grow research programs and teams, contribute to curriculum and governance, and represent the discipline internally and externally.

Build and scale AI-powered GTM systems and automations across Sales and Marketing. Design workflows, integrations, and enrichment pipelines to prioritize accounts, improve forecasting and pipeline visibility, automate repetitive processes, and deliver revenue intelligence and dashboards to drive better GTM decisions.

Design and run large-scale LLM evaluation and observability for production AI features: sampling, LLM-as-judge, human-in-the-loop labeling, monitoring, regression detection, and continuous improvement. Build LLM-powered root-cause analysis and recommended fixes, own feedback loops (prompt engineering, labeling, evaluation), enable teams with reusable tooling and docs, and partner with product, data science and people science to map measured quality to customer value.

Drive AI strategy and transformation by identifying high-value AI opportunities, defining roadmaps, operating models, and governance, facilitating workshops, building business cases, and supporting adoption, change management, and value realisation across business and technology stakeholders.

Lead client engagements to define and execute enterprise AI strategies, operating models, governance, and transformation roadmaps. Identify and prioritise high-value AI use cases, build business cases, drive adoption, mentor teams, and ensure measurable business outcomes across growth, efficiency, customer experience, and risk management.

The role involves delivering Data & AI solutions in marketing, leading client engagements, and developing strategies to enhance customer insights and experiences.

The AI Engineer will develop GenAI applications, oversee production rollouts, advise customers, present at conferences, and collaborate on product roadmaps.

Lead client engagements to design and implement practical AI governance frameworks, assess AI use cases for risk and compliance, embed governance into AI solution design, facilitate stakeholder workshops, and develop governance artefacts to enable responsible, scalable AI adoption.