Top Technology Jobs & Startup Jobs in Sydney

Lead and grow a team of approximately 10 AI engineers and engineering leads while guiding complex enterprise AI transformation engagements. The role combines people leadership, client consulting, technical and architectural judgment, and capability building. Responsibilities include coaching engineers, representing engineering expertise to senior stakeholders, translating AI strategies into production-ready solutions, and developing repeatable methodologies, practices, playbooks, and tooling for scalable consulting delivery.

Manage a portfolio of FMCG clients, serving as a trusted advisor on pricing, promotions, category management, and brand strategy. Deliver hands-on analysis using customer and shopper data, translate complex analytics into commercial recommendations, coordinate cross-functional teams, develop industry relationships, and support team members’ technical growth and career progression. The role requires liquor-sector expertise, strong communication, presentation, business development, and curiosity about emerging AI technologies.

Own a portfolio of media clients, building strategic relationships and embedding Quantium’s Media iQ products into planning, sales enablement, and measurement workflows. Drive product adoption, renewals, account health, and commercial value while translating data and insights into compelling business narratives. Identify adoption risks, develop expansion opportunities, advocate for client needs, and coordinate analytics, product, delivery, and governance teams.

Design and scale analytics solutions using data science, AI-native workflows, and cloud platforms. Develop models, algorithms, statistical analyses, and reusable AI-enabled approaches using Python and SQL. Evaluate AI-generated outputs, create technical specifications, support engineering delivery, mentor analysts, and improve workflows across distributed global teams.

Develop data science and AI-native analytical solutions using Python, SQL, cloud platforms, and AI tools. Responsibilities include data extraction and cleaning, feature engineering, model development, validation, testing, scalable solution design, and evaluation of AI-generated outputs. The role collaborates with analysts, engineers, and product specialists, contributes to project delivery and continuous improvement, and communicates technical concepts to non-technical audiences.

Senior HR Business Partner providing strategic HR support to Engineering: coach leaders on performance, ER, culture and change; shape people plans (resourcing, mobility, TA); use workforce analytics to inform actions; lead improvement initiatives and experiment with AI-enabled HR tools to increase impact.

Leads engineering delivery across fast-cycle client engagements, from scoping through execution, quality assurance, and outcome measurement. Partners with senior clients to translate technical complexity into commercial terms, guides architecture and quality decisions, and coaches distributed engineers across projects. The role requires strong consulting, full-stack or AI engineering credibility, stakeholder communication, adaptability, and end-to-end delivery ownership.

Own end-to-end talent acquisition for the Engineering organization, partnering with the CTO and senior technology leaders on hiring strategy, market intelligence, sourcing, and candidate experience. Build pipelines for hard-to-fill technical roles, improve recruitment processes and tools, support employer branding, and manage, coach, and develop a small team of technical recruiters.

Drive global financial planning and management reporting, including month-end close, divisional P&L reporting, OPEX analysis, forecasting, budgeting, and CFO reporting. Analyze financial performance, identify risks, provide recommendations, support finance transformation projects, and improve FP&A processes. The role requires advanced Excel and Anaplan skills, strong financial modeling capabilities, attention to detail, and effective cross-functional collaboration.

Leads the design and production delivery of generative AI solutions for clients. Manages and mentors data scientists, sets engineering standards, oversees solution quality and documentation, supports technical scoping and pre-sales, and helps shape reusable AI components and team strategy. Requires strong AI and machine learning expertise, production architecture experience, Python skills, cloud-native development knowledge, and commercial communication abilities.