Top AI Jobs in Sydney

Build and ship AI-native, agentic products end-to-end: design LLM-powered workflows, prototype with frontier models, collaborate with product/design/customers, ensure reliability through continuous shipping and on-call ownership, mentor engineers, and iterate based on customer feedback to scale intelligent agents into production.

Quota-carrying sales role focused on generating, qualifying, and closing AI opportunities across an assigned territory. Partner with field teams, build AI pipeline, craft executive pitch decks and proposals, leverage partner ecosystem, and maintain disciplined CRM and forecasting.

Serve as a technical strategic advisor embedding with strategic accounts to design and deliver enterprise agentic AI programs. Quantify and report value targets, manage program delivery and onboarding at scale, build centers of excellence, and ensure visibility on consumption and value metrics while maintaining strong customer relationships.

Embed with enterprise engineering teams to deploy and integrate Devin and agentic workflows, run workshops and pair-programming, quantify productivity impact, and scale customer learnings into repeatable playbooks and enablement materials.

Lead commercial growth and market adoption of AECOM's AI4Eng in Australia and New Zealand. Develop and execute go-to-market strategy, originate opportunities, build executive client relationships, hit revenue and profitability targets, scale operations, form strategic partnerships, represent the company externally, and build a multidisciplinary team to integrate AI-enabled engineering across the Buildings + Places sector.

This role leads enterprise-scale AI and Data transformation programs, acting as a trusted advisor to senior executives, and shaping data strategies and governance frameworks.

Lead Agentic Solution sales and presales teams to drive revenue for NiCE's AI and digital CX solutions (standalone or with CXone). Build territory plans, exceed targets, identify new opportunities, collaborate cross-functionally, analyze market trends, monitor sales metrics, and manage team hiring and separations.

Support sales by running discovery calls, technical deep dives, demos and POCs for AI and contact-center solutions; design recommended technical solutions, analyze requirements, provide technical guidance and training, and stay current on competitive landscape.

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.

Own and build a governed library of production-ready AI skills: write and test prompts and workflows, manage versioned repositories, create testing and release standards, track adoption and performance, and embed responsible AI practices. Work cross-functionally to translate requirements, join skills into end-to-end systems, maintain documentation and audits, and iterate based on real-world use.

Embed with enterprise clients to define outcomes and rapidly prototype production-grade agentic AI systems. Design RAG pipelines, multi-agent orchestration, and LLM assistants using Amazon Bedrock and SageMaker. Deploy end-to-end integrations into enterprise platforms while building responsible AI controls, evaluation pipelines and compliance for regulated industries.

Design and build connectors, tool integrations, and real-time data pipelines to enable LLM-based agents to act on analytics, SEO, content, and marketing platforms. Develop reusable agent skills, evaluate agent performance against MAU and ARR, iterate with Country Managers, replace manual processes with live tooling, and document frameworks for repeatable market deployment.

Provide pre-sales architecture and technical consulting for AI/HPC networking and infrastructure across Australia/NZ. Lead scoping workshops, design networks for large GPU clusters, assess data center fit-out, build OEM relationships, and deliver high-quality AI infrastructure solutions.

Embed with clients to discover high-value agent use cases, design and build production-grade agentic architectures (orchestration, data hydration, semantic layers), implement verification and governance, manage stakeholder expectations, and capture reusable playbooks and eval suites for future engagements.

Own and improve an embedded Linux Edge AI sensor platform: Yocto builds, kernel/drivers, device trees, hardware integration (cameras, microphones, modems, sensors), OTA and provisioning, device security, profiling and optimizing Edge ML inference (NPU/quantisation), audio analysis, and backend services for fleet diagnostics, observability and deployment. Collaborate with hardware, AI, cloud and manufacturing teams from concept through field deployment.

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.

Drive visual AI quality by annotating and evaluating large visual datasets, developing scoring rubrics, identifying failure modes, and translating design critique into structured feedback for ML engineers. Use generative tools to prototype, contribute to taxonomies, and maintain high standards of annotation documentation to improve model performance and aesthetic alignment.

Own and grow ANZ BFSI accounts by executing value-based, consultative sales (MEDDPICC) with C-level and data/AI stakeholders. Land new enterprise logos, expand within existing accounts, coordinate Pre-Sales, Marketing and Customer Success for POVs, and align co-sell motions with hyperscalers and GSIs while maintaining rigorous forecasting in Salesforce.com.

Support marketing and growth teams to create AI-generated content, plan and schedule social posts, build email campaigns and automation, manage CRM segmentation, repurpose content, conduct SEO and competitor research, monitor campaign performance and reporting, document processes and prompts, and assist with webinar and partner marketing.

Support building AI-powered, no-code/low-code workflow automations across marketing, sales, customer success, and internal ops. Help automate CRM and repetitive tasks, assist AI-assisted research, test and document workflows, and collaborate with cross-functional teams to improve business processes.

Work with AI engineers to build, test, and improve production AI workflows that automate business processes, integrate with APIs and data stores, develop simple LLM-based applications, optimize prompts and structured outputs, and deliver at least one functional AI automation project during the internship.

Pre-sales technical architect for AI engagements: translate customer requirements into end-to-end AI solution designs, reference architectures, BOMs and PoC plans; validate GPU/compute, networking, storage and software stacks; coordinate ATC labs and partner integrations; enable field teams and ensure clean handoff to delivery.

Serve as the technical pre-sales lead within regional AI pods, designing end-to-end AI architectures (GPU/compute, networking, storage, software, MLOps), creating BOMs and PoC plans, coordinating ATC lab engagements, validating designs with NVIDIA and cloud partners, and ensuring clean handoffs to delivery teams to advance deals.

Serve as the pre-sales consulting partner in regional AI pods to uncover business needs, scope and position AI services (AI Factory, AI Foundations, Workforce AI, AI Native Engineering), build pipeline, develop business cases and TCO analyses, design ATC lab/PoC engagements, and ensure continuity from pre-sales to delivery while collaborating with sales, architects, and delivery teams.

Pre-sales consulting role driving AI services engagements across AI Factory, AI Foundations, Workforce AI, and AI Native Engineering. Uncover client needs, scope and position consulting services, build business cases and TCO analyses, design ATC lab PoCs, and ensure continuity between pre-sales and delivery while collaborating with sales, architects, and delivery teams.