Top AI Jobs in Sydney

Manage multilingual data collection and Large Language Model evaluation projects, ensuring quality assurance and effective global team coordination.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

The Senior Software Engineer in Test builds and executes automated tests, develops testing tools, and collaborates on technical designs while ensuring system testability for the TraceLink platform.

Lead AI development projects, focusing on generative AI solutions and cloud-native engineering. Collaborate with teams to deliver innovative software solutions.

Lead and build production-grade AI systems (LLMs and foundation models) for small business applications. Design, deploy, and monitor scalable ML solutions (document understanding, forecasting, conversational interfaces) on AWS, implement MLOps best practices, and mentor a small engineering team to deliver reliable, secure, customer-focused features.

Design, build and deploy LLM- and foundation-model-based ML systems for document understanding, forecasting and conversational interfaces. Own end-to-end MLOps workflows, optimise for scalability, safety and reliability on AWS, and collaborate with product and engineering to take features from concept to production.

Lead a small AI engineering team to design, build, deploy and monitor LLM- and foundation-model-based ML systems for MYOB's SaaS platform. Implement MLOps best practices on AWS (SageMaker, Bedrock, S3), optimise for scalability, safety and reliability, and drive projects from ideation to production while collaborating with product and engineering stakeholders.

Embed with enterprise clients to architect, prototype, and deploy agentic multi-agent AI systems and RAG workflows. Re-engineer business processes into human-in-the-loop and autonomous AI workers, integrate cloud, data pipelines, and frontier LLMs, and advise executives on rollout and risk-managed adoption.

Design and implement complex backend services for Binance Square. Collaborate with product, DevOps, and QA to deliver high-quality microservices, promote engineering best practices, and perform code reviews.

Early-career intern will support AI projects for compliance and risk (KYC, KYB, EDD). Tasks include testing and optimizing LLM/Agent workflows, reviewing prompts and model outputs, documenting findings and edge cases, supporting small-scale implementations, and performing operational analysis to improve processes.

Join as an early-career full stack engineer to build frontend and backend product features, integrate AI coding tools into development workflows, translate product requirements into implementations, and grow toward autonomous full stack delivery while improving cross-team processes.

The AI Creative Designer creates high-quality, AI-generated visuals for marketing campaigns, collaborating with teams to optimize visual content for conversion rates.

The Senior AI/ML Engineer will design, develop, and deploy language models for African languages, focusing on NLP applications and cultural context.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

The Senior .Net Developer will enhance SDG's C#/.NET Core codebase, design high-load services, and optimize MS SQL queries, benefiting from a remote work environment and attractive benefits.

Design and productionize context-aware autonomous conversational agents on GCP. Build RAG and knowledge-graph backed retrieval, manage complex multi-turn dialogue states, integrate real-time APIs, scale Vertex AI/LLM workflows, and provide technical leadership and mentoring.

Design, build, and deploy production-grade AI solutions (agents, RAG, MCP servers). Analyse business processes, integrate APIs and cloud platforms, establish prompt engineering and developer standards, manage projects, and upskill client teams.

Leads end-to-end delivery of production AI and machine learning solutions, owning architecture for LLM, RAG, embeddings, vector databases, and APIs. Mentors engineers, translates business needs into scalable technical solutions, oversees MLOps, CI/CD, monitoring, and reliability, conducts code reviews, and collaborates with stakeholders. The role remains hands-on through prototyping, troubleshooting, and development support.

The Software Engineer will implement, configure and deliver AI solutions, focusing on integrations and conversational AI across the NICE CXone ecosystem, while ensuring quality and problem-solving in a collaborative environment.

Lead engineering delivery for an Apigee X AI gateway that fronts LLM inference across multi-cloud providers. Translate architecture into epics, build OpenAI-compatible API capabilities, implement provider abstractions (Vertex AI, Bedrock), secure multi-cloud traffic, use Terraform and GCP services, mentor engineers, and manage stakeholder communications, runbooks, and CI/CD/testing standards.

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.

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.

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.