AI Architect Lead — Enterprise GenAI & Scalable Solutions

CO001 Cuscal Limited; Australia; Sur place; AUD 180 000 - 260 000; Plein temps

Avantages offerts par ce poste

IGNITE development opportunities

Cuscal Advantage discounts

Flexible work arrangements

Diversity & inclusion

Résumé du poste

Cuscal Limited in Australia is seeking an experienced AI Architect to lead enterprise AI initiatives on a 12-month maximum term contract. You will translate business needs into scalable designs, guide architecture decisions and drive secure, governable solutions.

You’ll work across technology, data and business teams, build AI apps using LLMs and RAG, assess models for performance and cost, and ensure Responsible AI principles are embedded throughout.

Qualifications

• Experience designing enterprise AI solutions and architecture reviews.
• Ability to translate business requirements into scalable AI designs.
• Strong software engineering and integration design skills.

Responsabilités

• Design, build, test, deploy and support AI and Generative AI solutions
• Act as the AI architect and Tech Lead for key initiatives
• Build applications using LLMs, ML models and AI services
• Design agentic AI solutions capable of reasoning and tool use
• Develop Retrieval-Augmented Generation (RAG) solutions
• Work with prompt engineering, tool calls and model orchestration
• Integrate AI apps with APIs, databases and enterprise systems
• Evaluate AI models for performance, security and cost
• Embed security, data governance and Responsible AI principles
• Develop reusable AI architecture patterns and documentation

Connaissances

AI architecture

Solution design

Stakeholder engagement

Software engineering

Outils

Azure Foundry

Description du poste

Cuscal Limited in Australia is seeking an experienced AI Architect to lead enterprise AI initiatives on a 12-month maximum term contract. You will translate business needs into scalable designs, guide architecture decisions and drive secure, governable solutions.

You’ll work across technology, data and business teams, build AI apps using LLMs and RAG, assess models for performance and cost, and ensure Responsible AI principles are embedded throughout.