Application closing date: Friday, 20 November 2026 • 11:59pm, Canberra time Estimated start date: Monday, 11 January 2027 Location of work: QLD Working arrangements: Full-time onsite for the first 6 weeks. A hybrid WFH arrangement, usually a minimum of 2 days per week onsite, will be considered from the location of their capital city. Length of contract: 12 months Contract extensions: Up to a maximum of 24 months Security clearance: Must have an active Baseline clearance Rates: $140 - $160 per hour (inc. super) Services Australia is at the frontline of government service delivery, supporting millions of Australians, and is front and centre of a vision to be a world leader in government service delivery. It’s using cutting-edge technology to build world class platforms and capabilities to help Australians get on with their lives. The Senior Artificial Intelligence (AI) Architect provides enterprise level architecture leadership for the agency’s adoption of AI. The role shapes AI architecture strategy and delivers secure, scalable and responsible architecture solutions aligned with business priorities and enterprise architecture. The role translates requirements and operational needs into practical AI capabilities, establishes reusable patterns and governance, and guides integration across data, technology and business processes. It supports improved service delivery, workforce productivity and decision-making while reducing implementation risk and enabling safe, sustainable AI adoption at scale. Key duties and responsibilities: - Develop and maintain the agency’s AI architecture strategy, target architecture, principles, standards, reference architectures, reusable patterns and roadmaps. - Translate business, policy, service delivery and ICT requirements into secure, scalable, resilient and supportable end-to-end AI architectures, supported by clear options, decision records and implementation guidance. - Assess AI opportunities, platforms, models and tools against strategic alignment, business and public value, feasibility, data readiness, interoperability, cost, risk, performance, supportability and vendor dependency. - Define and assure architecture patterns, guardrails and controls across the AI lifecycle for generative AI, large language models, retrieval-augmented generation, machine learning, intelligent automation and emerging AI technologies. - Provide architecture assurance and clear advice on options, trade-offs and risks to senior stakeholders and governance forums, collaborating across business, architecture, data, cyber security, privacy, legal, procurement, delivery and operations. - Build APS capability through mentoring, workshops, architecture walkthroughs, reusable guidance, templates and structured knowledge transfer. Knowledge / Qualifications required: - Strong knowledge across enterprise and solution architecture practices, methods and governance applicable to large, complex organisations. - Strong knowledge across enterprise and solution architecture practices, methods and governance applicable to large, complex organisations. - Strong knowledge of AI security, assurance, privacy, governance and regulatory obligations relevant to government and regulated environments. - Strong knowledge of AI SDLC practices and the architecture, engineering and governance considerations required to transition AI solutions from experimentation through to production - Understanding of contemporary AI delivery and operations, including machine learning operations, large language model operations, agentic, model monitoring, service management and technology risk management. - Ability to communicate, negotiate and influence effectively with executives, governance bodies, technical specialists, delivery teams and business stakeholders. - Ability to work through ambiguity, resolve competing priorities and provide clear, evidence-based architecture recommendations. - Relevant tertiary qualifications or recognised certifications in architecture, information technology, artificial intelligence, machine learning, computer science, data science, engineering, cloud or cyber security would be advantageous. Technical skills required: - Ability to develop AI strategies, roadmaps, reference, platform and AI security architectures, reusable patterns, options assessments and architecture decision records. - Ability to define, support and assure responsible AI, privacy, security, data governance, human oversight, auditability and model-risk controls. - Ability to evaluate AI platforms, models, tools and vendors against business needs, technical feasibility, interoperability, performance, cost, supportability and value for money. - Ability to define and assure non-functional requirements for AI services, including availability, resilience, capacity, latency, observability, maintainability and disaster recovery. Essential criteria - Demonstrated ability to analyse complex business issues within the cyber...