Top AI Jobs in Sydney

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.

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.

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.

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.

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.

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%.

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.

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.

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.

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.

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.

Provide on‑demand coaching and small‑group training to accelerate enterprise AI adoption (Microsoft Copilot, Gemini, Claude). Develop micro‑training resources, monitor usage, collect feedback, guide responsible AI governance, and help employees apply AI to everyday tasks.

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.

Own and evolve the AI-native platform and developer experience: build CI/CD, build/test/deploy loops, agent-safe sandboxes, cloud infra and cost controls, SLOs and observability, incident response, and platform capabilities that multiply engineering productivity across teams.

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.

The role requires defining and evolving the architecture for enterprise platforms, collaborating with teams on integration patterns, and ensuring solutions are scalable and secure.

As a Senior Software Engineer at Fetch, you'll build AI-driven products to improve pet health, mentor engineers, and develop event-driven architectures. You'll collaborate with teams to deliver impactful features and ensure reliability and observability in the systems you create.

Join Fetch as a Software Engineer to build AI-driven products that enhance pet health and streamline veterinary care, working with a collaborative team.

Quota-carrying enterprise sales role focused on generating, qualifying, and closing AI opportunities within assigned territory. Partner with field teams and technology partners, craft executive presentations and proposals, manage pipeline and CRM, and coordinate AI GTM resources to win deals.

Lead technical direction for AI-native agent products, solve high-leverage engineering problems, improve reliability and evaluation, partner with product and customer teams, mentor engineers, and ship production-grade autonomous agent features rapidly.