Top AI Jobs in Sydney

Provide technical pre-sales and architecture support for AI/HPC networking solutions across Australia and New Zealand. Scope requirements, design high-performance network and data center solutions (including power, cooling, cabling), build OEM relationships, advise customers on architectures supporting large GPU clusters, and identify services opportunities.

Lead design and implementation of AFCA's AI governance and assurance framework. Establish lifecycle assurance, define controls and evidence requirements, conduct technical risk and fairness/robustness evaluations, maintain AI inventory and risk register, report to executives and uplift organisation-wide AI governance capability through guidance, education and stakeholder collaboration.

Lead Datacom's AI Centre of Enablement programme management: prioritize AI use cases, build business cases, own the AI backlog, govern delivery, track benefits realisation, and manage a rotating team of project managers to scale AI initiatives across the business.

Build production AI-native systems for BJAK's Neobank: agents, LLM apps, RAG, tool-calling and automations for onboarding, KYC, support, risk, CRM and ops. Work with product and engineering to ship reliable, evaluated, secure, low-latency AI workflows that scale and reduce manual work.

Design and build backend services, APIs and workflows for an AI neobank. Support payments, wallet, savings, investing, insurance and partner integrations. Ensure reliability, security, observability and performance. Collaborate with product, mobile and operations teams to deliver customer-facing journeys and regulated financial product infrastructure at scale.

Build and productionize AI-native workflows, assistants, agents and automation across fintech product and operational areas. Integrate LLMs, internal data, APIs and knowledge bases; design evaluation, monitoring and fallback flows; prototype, test with users, and deploy reliable AI systems to improve customer support, CRM, onboarding and operations.

Build end-to-end customer-facing and internal features for an AI neobank: web flows, backend APIs, admin tools, dashboards, and operational systems. Integrate APIs, handle data flows, improve production reliability, use analytics and feedback to iterate, and support products across payments, savings, investing, insurance and travel.

The Senior AI Engineer will design and implement end-to-end AI solutions and LLM applications, ensuring production-grade reliability while collaborating with customers and technical teams.

Lead end-to-end solution architecture for data, analytics and AI initiatives; translate enterprise strategy into scalable designs; embed security, privacy, governance and responsible AI; provide hands-on leadership across data platforms, integration, modelling, serving and reporting; guide teams on design patterns, risks and architectural roadmaps in a regulated environment.

Contract role contributing design expertise to visual AI: annotate and label visual data, evaluate AI outputs for aesthetics and usability, develop scoring rubrics, identify failure modes, provide structured feedback to ML teams, and maintain high-quality documentation.

Embed with enterprise clients to define outcomes and rapidly deliver production-grade AI solutions. Design and build agentic systems (LLMs, RAG, multi-agent orchestration), use Amazon Bedrock and SageMaker for model development and lifecycle, implement vector retrieval and evaluation pipelines, integrate into enterprise platforms, and ensure responsible AI and regulatory compliance.

Partner with strategic customers to identify high-value Generative AI use cases, build prototypes, and drive solutions from prototype to production using OpenAI technologies. Provide technical leadership, enterprise architecture guidance, stakeholder management, and feedback to Product and Research teams while scaling best practices and developer resources.

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.

Build native Android features for BJAK's AI Neobank using Kotlin and modern Android tools. Integrate backend APIs, improve performance and reliability, collaborate with product/design, use analytics to refine UX, and implement on-device AI experiences where valuable.

Build and ship native iOS features in Swift for an AI-enabled neobank app. Design clean mobile flows for payments, insurance and financial services, integrate backend APIs, improve performance and reliability, use analytics and on-device AI where it enhances UX, and collaborate with product and design to simplify journeys.

Build and ship native Android features in Kotlin for an AI-enabled neobank: design clean user flows, integrate backend APIs, improve performance and reliability, use analytics to iterate, and implement on-device AI where it improves UX.

Serve as Snowflake technical expert for AI/ML workloads: design and build ML/GenAI pipelines, create hands-on POCs using SQL/Python/APIs, enable customers and SIs, resolve technical challenges, and collaborate with product and engineering. Travel to customers ~25%.

Join Scyne Advisory's Data & AI team to build cloud and analytics solutions using Python and SQL, apply GenAI/LLM tools (Gemini, Claude) for research and code generation, translate stakeholder needs into solution designs, and collaborate in agile teams while learning AI ethics and consulting practices.

Lead AMP's enterprise AI risk program: shape governance, inventory, observability, assurance and reporting; embed AI risk controls across business, technology, data, security and risk; influence senior stakeholders and committees; uplift frameworks, policies and controls to meet regulatory obligations while enabling responsible innovation.

Lead AI adoption and stabilization for enterprise contact center customers. Execute adoption playbooks, optimize AI outputs (prompt engineering, knowledge alignment, workflow tuning), validate UAT and trust indicators, analyze usage and KPI data to surface optimizations, build adoption scorecards, and lead cross-regional stakeholder sessions to drive sustained usage and product feedback.

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 organisation-wide AI strategy, select and standardise AI platforms (Microsoft-focused), establish Responsible AI governance, prioritise enterprise use cases, guide MLOps and scalable deployments, and advise executives while ensuring security, compliance, and measurable business outcomes.

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.

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.

Design, build, and deploy end-to-end AI solutions including predictive ML, GenAI, RAG, and agentic systems. Own data preparation, feature engineering, model development, deployment, monitoring, and customer enablement. Build scalable backend services and APIs, implement production-grade GenAI pipelines, and guide customers on governance, evaluation, and adoption while collaborating with product and engineering teams.