Senior AI Architect

• Initial Contract Duration: Up to 12 months
  
• Extension term details: Up to a maximum of 24 months
  
• Location: QLD, WA, ACT, VIC, NSW, SA
  
• Security Requirements: Must have Baseline
  
• Working Arrangements: Hybrid
  The Labour Hire Worker is expected to work onsite for the first 6 weeks before a hybrid flexible working arrangement can be considered, unless otherwise negotiated. A hybrid flexible working arrangement may then be considered, ensuring the Labour Hire Worker’s residing address is within reasonable travel time and distance of the RFQ location to present onsite in cases of emergency or to meet business requirements. The location is the capital city of selected state/s.
• Maximum hours: Standard working hours are 40 hours per week. Workers may be required to work additional hours, provided the total working hours do not exceed a maximum of 80 hours per week.
  

Job details

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

Duties may include some or all of the following:

• 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

• 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

• 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.
  
• Applied knowledge of Generative AI, LLMs, RAG, machine learning and agentic AI, including evaluation, testing, deployment, monitoring and optimisation practices.
  
• Strong capability across data, application, integration, cloud, infrastructure, identity and cyber security architecture, with the ability to design scalable, resilient and supportable end-to-end AI solutions.
  

• Enterprise AI architecture and solution design: Demonstrated experience developing enterprise-scale, end-to-end AI architectures in complex environments, including architecture strategies, roadmaps, platform and reference architectures, patterns and decision records across data, models, applications, integration, cloud, infrastructure, cyber security and operations.
  
• AI technology and lifecycle architecture: Demonstrated applied knowledge of generative AI, large language models, machine learning, retrieval-augmented generation, agentic and AI lifecycle management, including evaluation, implementation, testing, monitoring, optimisation and operational support.
  
• Secure, responsible and risk-based and resilient AI design: Demonstrated ability to design secure, scalable, resilient, supportable and cost-effective AI solutions aligned with enterprise architecture, cyber security, privacy, responsible AI, performance, availability and operational requirements. Responses should include evidence of evaluating options, risks, trade-offs and controls.
  
• Architecture leadership, communication and capability transfer: Demonstrated experience providing clear architecture advice to senior stakeholders and governance forums, influencing decisions, collaborating across multidisciplinary teams and transferring knowledge through documented artefacts, workshops, mentoring, reusable methods and templates.
  

Desirable Criteria

• Experience delivering AI architecture within the Australian Government or another large, complex and highly regulated environment or industry.
  
• Experience developing AI strategies, target-state architectures, investment roadmaps and platform or product evaluations that consider feasibility, benefits, cost, risk and public value.
  
• Experience progressing AI capabilities beyond proof of concept into secure, monitored and scalable production services.
  
• Relevant tertiary qualifications or recognised certifications in architecture, information technology, artificial intelligence, machine learning, computer science, data science, engineering, cloud or cyber security.
  

If you wish to have a confidential discussion, call us on 02 6108 3980 or 0410 756 040 for more information.