Solution Architect - AI & Data Architecture

About the role

Qantas is looking for a Solution Architect to join its Data, AI and Integrations architecture team at the Qantas Head Campus in Mascot. You will shape how the Qantas Group designs, governs and scales AI, set the architecture for the enterprise GenAI platform and AI/ML workbench, and ensure AI solutions are built on well-governed data from the new Snowflake-based data platform. This is a permanent, full-time position.

Key responsibilities

• Lead the solution architecture for AI and ML initiatives, from generative and agentic AI to predictive ML, and steer them through architecture review.
• Maintain the AI capability model and logical architecture and contribute to the AI and ML reference architecture.
• Design the enterprise GenAI platform and AI/ML workbench, covering model access, agent orchestration, retrieval patterns and tool integration (including Model Context Protocol).
• Build AI governance into every design, including privacy by design, data residency, model inference location, human oversight, evaluation and monitoring.
• Define patterns for AI on the data platform, including Snowflake Cortex AI and Snowpark ML, and for real-time inference using event streaming.
• Assess build versus buy and managed versus self-hosted options, with clear cost, risk and value trade-offs.
• Partner with Security, Cyber and Risk on AI-specific threats such as prompt injection, data leakage and model supply-chain risk.
• Advise sponsors and delivery leads on scope, sequencing and architecture risk across concurrent AI initiatives.
• Mentor architects and engineers to build AI architecture capability.

Required profile

• At least 7 years in solution or enterprise architecture, including recent hands-on experience designing and deploying AI/ML solutions in production on AWS (e.g., Amazon Bedrock, Bedrock Agent Core, SageMaker AI).
• Strong data management foundations, including data quality, master and reference data, lineage and cataloguing, and an understanding of how these affect model accuracy, bias and reliability.
• Working knowledge of the Australian Privacy Principles (including cross-border disclosure) and Australian Government AI guidance, translated into architecture controls.
• Ability to explain AI trade-offs to executives in plain language, and sound judgement in a large matrix organisation across agile and traditional delivery.

Required skills

• Generative and agentic AI patterns: RAG, fine-tuning, agent frameworks, evaluation, guardrails and inference cost management.
• MLOps and model lifecycle management within program governance.
• TOGAF or an equivalent framework.
• Desirable: Snowflake (Cortex AI, Snowpark ML), Kafka or Confluent, Alation or a similar data catalogue, and a background in aviation, transport or another regulated, safety-critical industry.

What we offer

• On-the-job training and coaching plus formal training opportunities.
• Discounted air travel within Australia and abroad, accommodation and holiday deals.
• Flexible leave, including 18 weeks paid parental leave.
• Access to rewards and salary packaging.
• Wellbeing support, including a tailored nutrition plan and mental health resources.