Top AI Jobs in Melbourne

Design, implement, and optimize AI-powered workflows and integrations across HubSpot, Actionstep, and third-party tools. Automate lead management, client intake, document generation, task assignment, reporting, and maintain integration performance and documentation while collaborating with stakeholders and legal teams.

Lead engineering for an AI-native Web3 product: ship production features, turn AI-assisted prototypes into scalable systems, own architecture/security/quality, direct AI coding agents, define engineering standards, and collaborate with founders on product and technical strategy.

This job is for candidates with AI infrastructure experience to submit their resumes for future opportunities. No specific role is posted.

Lead product strategy and execution for AI and personalisation initiatives. Define vision, prioritise experiments, optimise channel performance, and drive measurable commercial growth through cross-functional collaboration, data-driven decisions, and stakeholder influence.

Build AI-powered client products from discovery through production using full-stack engineering, AI coding tools, prompt and context engineering, and critical validation of generated outputs. Develop frontend and backend features, support testing, QA, DevOps, and CI/CD, while collaborating directly with client engineering, product, and domain teams. Translate ambiguous business needs into production-ready systems, communicate clearly with stakeholders, and contribute to consulting engagements in a hybrid Sydney-based environment.

APAC specialist overlay driving growth of Sprinklr's CCaaS and Agentic AI: partner with account teams, create pipeline, lead solution selling, engage senior CX and IT stakeholders, and build partner ecosystem to win complex enterprise deals.

Define and execute the product roadmap for AI-driven on-chain monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, ensure timely delivery of features, and communicate roadmap progress to stakeholders to improve blockchain security offerings.

Provide specialist legal advice on cyber preparedness and incident response, complex data/privacy matters, AI governance, regulatory investigations and enforcement. Work with cross-firm teams to advise boards and executives, manage large matters, lead teams, and support business development.

Lead design and delivery of scalable data and AI platforms across Azure and Databricks. Architect production-grade ML/LLM solutions (RAG, agentic patterns), build batch and streaming pipelines, formalize medallion/lakehouse standards, implement MLOps/DataOps (CI/CD, monitoring, orchestration), embed Responsible AI and governance, and provide technical leadership, mentoring, and cross-functional delivery.

As an Applied AI Engineer, you'll build AI agents and experiences from concept to production, collaborating across teams and optimizing systems for usability and quality.

Partner with business stakeholders to identify AI opportunities, rapidly develop proofs of concept and scalable AI-enabled solutions using approved AI platforms, low-code and automation tools. Drive adoption through workshops, demos, reusable prompts/templates, and coaching while ensuring solutions meet Responsible AI, security, privacy, and governance standards and deliver measurable business value.

Work with stakeholders to discover practical AI use cases, prototype and deliver lightweight LLM-enabled agents, troubleshoot and refine solutions, facilitate stakeholder adoption and training, and ensure responsible AI governance. Own projects from discovery through delivery to measurable outcomes while communicating trade-offs and limitations clearly.

Lead end-to-end customer deployments of Cresta's AI SaaS platform across APAC, manage complex, customer-facing projects, define success metrics, ensure smooth launches, drive adoption, and collaborate with product, engineering, and GTM teams to scale AI solutions.

Drive consultative B2B SaaS sales for ConvAI by leading discovery calls, demonstrating the Oration platform, building ROI-based business cases, creating tailored proposals and SOWs, and managing the pipeline to close deals using Salesforce.

Drive renewals, adoption and growth of Microsoft 365 and AI solutions. Lead renewal negotiations, manage stakeholders, identify upsell opportunities, maintain forecasts, collaborate with sales, customer success and Microsoft, and improve processes to maximise customer value.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

Lead organic search and AI visibility strategy for multiple partner websites, driving SEO performance, reporting, and growth in leads and enrolments.

Build and maintain front end systems for Matilda's public product, focusing on user experience, performance, and reliable interactions.

The AI Researcher will design architectures, run experiments, evaluate large language models, and collaborate with ML engineers for model training and analysis.

Build and operate production AI systems that ingest event-level revenue and telemetry, ensure data quality, run experimentation, investigate failures, and provide agent-enabled analytics and automation to improve business decisions.

As an AI/ML Engineer, you will develop and optimize AI solutions for renewable energy assets, collaborating with a skilled team to deploy algorithms in real-world projects.

Freelance AI Evaluators converse with AI chatbots and language models to assess capabilities, safety, and helpfulness. Work includes structured written and voice interactions, submitting ratings, screenshots, recordings or write-ups per task specifications, and completing language and evaluation assessments to inform model development.

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.

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.

Lead design and delivery of scalable AI and data solutions, set engineering standards and guardrails, experiment with emerging AI tools, collaborate with product stakeholders, mentor engineers, and improve platform performance, reliability and cost across cloud-based pipelines.