Senior AI Engineer [T500-26833]
Job Description
About Officeworks:
Officeworks' purpose is "we bring big ideas to life at low prices". We are Australia's leading omnichannel retailer of complete technology solutions, stationery, furniture, art supplies, and learning resources. We also offer services including Print & Create and Geeks2U. We begin with customers—our products and services provide solutions to our diverse range of customers across Australia, from households, students, small to large-sized businesses, governments, and schools.
Why this role exists:
The Senior AI Engineer is a foundational technical role within a brand-new AI capability. This role is responsible for executing the technical transition from traditional machine learning (ML) to modern, generative AI. This role will build and deploy sophisticated agentic systems, leveraging Large Language Models (LLMs), multi-step reasoning, and Retrieval-Augmented Generation (RAG), to drive Officeworks' transition toward a democratized, self-serve analytics model.
Where you will make a difference:
In this role you will:
AI & Agentic Systems Development:
Build ML and LLM systems utilizing Vertex AI and the broader Google Cloud models.
Develop complex agentic workflows, including RAG, tool use, multi-step reasoning, and autonomous agents.
Implement Model Context Protocol (MCP) components, such as API tools, vector memory, and data resources.
Adapt existing ML systems to support modern AI architectures, ensuring a smooth transition from legacy data roles.
Engineering & MLOps Excellence:
Deploy and manage AI solutions via GitHub and Cloud Run, embedding robust MLOps/LLMOps practices.
Engineer prompting strategies, guardrails, and constraint management to ensure system safety, low latency, and cost-efficiency.
Oversee scalable data pipelines within Snowflake as the primary enterprise platform for AI and data teams.
Ensure technical output control and rigorous testing to maintain high quality and reliability of AI features.
Leadership & Continuous Improvement:
Foster an engineering culture focusing on results and technical excellence.
Identify and execute process improvement opportunities within the AI development lifecycle to increase delivery velocity.
Possess a continuous improvement mindset, proactively identifying anomalies through data profiling to enhance model accuracy.
Ensure all institutional knowledge and technical IP is rigorously documented to support long-term team sustainability.
Who you will be working with:
AI Technical Associate Manager: Partnering on the design and execution of future-state agentic architectures.
Data & Analytics Hubs: Collaborating with Data Architects, Modellers, and Cloud Engineers.
Officeworks Leadership: Coordinating with leaders to ensure delivery aligns with enterprise data strategy.
What success looks like:
Technical Innovation: Successful deployment of RAG and agentic workflows that drive measurable commercial value.
Operational Flow: Robust MLOps pipelines that ensure secure, cost-effective, and low-latency AI performance.
Data Democratization: AI solutions that directly support the shift toward a self-serve analytics model for the business.
Sustainable IP: A clear, documented architecture that effectively captures institutional knowledge within the permanent hub.
How you will lead:
Individual Contributor:
Lives our Officeworks values and behaviors
Proactively contributes to a safe working environment, escalates appropriately if there are unsafe conditions or inappropriate behaviour
Operates in line with applicable Officeworks company policies and Code of Conduct
Demonstrates a strong sense of personal accountability and curiosity to learn and develop
Qualifications and work experience:
Essential:
Education: Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field.
Experience: 6+ years of experience in machine learning (ML) systems knowledge and building scalable data pipelines.
Adaptability: A proven ability to understand and execute the transition from traditional ML to generative AI and agentic systems.
Technical Mastery: Deep hands-on experience with GitHub, Snowflake, and ML system architectures is essential.
Cloud Proficiency: Expertise in Vertex AI, Cloud Run, and GCP/BigQuery environments.
Preferred:
Advanced AI: Experience with MCP, multi-step reasoning agents, and advanced prompt engineering.
Retail Context: Familiarity with high-volume retail data environments and SAP integrations.
