AI / ML Engineer

The core responsibilities for the job include the following:

AI and 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 and 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 and 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 and Analytics Hubs: Collaborating with data architects, modelers, 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.

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

Requirements:

• 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.