Position Description: Senior AI Engineer 

Department: Technology – Enterprise Systems

Reports To: Lead Architect – AI & Integration 

Location: Brisbane

Employment Type: Full-Time – 12 Month Contract 

Role Purpose

We’re looking for a hands-on AI engineer to help design, build, and scale Stanmore’s enterprise AI and integration platforms. This role is for someone who loves building and developing solutions, agents, data pipelines, and integrations that make a real difference. You’ll work closely with the Lead Architect and broader team to turn ideas into production-ready systems.

You’ll contribute to how AI and automation are applied across both corporate and operational environments, building practical systems that lift productivity, strengthen decision-making, and modernise the way we work.

You’ll collaborate with outsourced teams and internal specialists, build strong working relationships across the business, and help ensure solutions are secure, scalable, and aligned with Stanmore’s enterprise strategy. If you want to make a meaningful impact on our digital future, this is the role to do it.

Key Responsibilities

AI Engineering & Solution Delivery

• Design and build AI systems, agentic workflows, agents, and automation solutions using Azure OpenAI and Azure AI Services (including Azure AI Search, Document Intelligence, Cognitive Services, etc.), Semantic Kernel, and modern orchestration frameworks.
• Develop hands-on prototypes, POCs, and production-ready AI components.
• Contribute to the technical architecture for AI initiatives and ensure alignment with business strategy and platform guardrails.
• Produce reusable AI frameworks (prompts, patterns, agent behaviours, integration flows).
• Provide hands-on engineering support across critical phases of design and delivery.

Contribute to the AI Center of Excellence (AI CoE)

• Participate in AI CoE activities, contributing technical input on AI standards, governance, and prioritisation.
• Support the AI CoE operating rhythm:
  • Technical standards & architecture reviews
  • Governance & guardrails
  • Use case intake & prioritisation
  • Delivery assurance
  • Pattern development & knowledge sharing
• Help maintain and apply the Stanmore AI Guardrails, including security, ethical AI, privacy, data controls, and responsible AI.
• Follow established delivery models to ensure AI work is consistent, repeatable, and scalable.
• Represent the AI engineering team in technical discussions and knowledge-sharing sessions.

Integration & Data Engineering

• Develop and maintain APIs, event-driven patterns, and cloud-native integrations across systems such as SAP, ServiceNow, Ariba, Minestar, and core corporate/operational platforms.
• Build reference solutions using Azure Functions, APIM, Data Factory, Event Hub, and Service Bus.
• Support the development of standard data models, data agreements, and metadata frameworks for AI, reporting, and operational systems. Build or support the development of data pipelines, transformation logic, and ingestion frameworks.

Technical Collaboration & Quality

• Participate in code reviews, pair programming, and building components to a high standard.
• Share knowledge with peers and contribute to team upskilling through documentation and collaboration.
• Follow and champion high standards in engineering, DevOps, IaC, observability, and quality practices.
• Help document architecture decisions and ensure they are clearly communicated within the team.

Delivery & Execution

• Contribute to architecture artefacts including solution designs, sequence diagrams, models, and operational readiness documentation.
• Work with business partners and the Lead Architect to understand requirements and contribute to technical plans.
• Support delivery squads with hands-on problem solving and technical guidance.
• Ensure solutions meet performance, security, safety, reliability, and cost objectives.

Standards, Governance & Security

• Follow and contribute to enterprise AI and integration patterns, guardrails, and architectural blueprints.
• Ensure responsible AI, cyber security, privacy, and data governance are embedded into every solution.
• Contribute to documentation on AI standards, decision frameworks, and supported tools.
• Participate in architecture reviews and provide technical input on AI-related projects.

Essential Skills & Experience

Required (Hands-On Capability Mandatory)

• Minimum 5 years in engineering roles with solid hands-on cloud engineering skills.
• Strong implementation experience with Microsoft Azure, including:
  • Azure OpenAI
  • APIM, Functions, Service Bus, Event Grid
  • Azure Data Lake, Fabric, Data Factory
  • Azure AI Search & vector databases

• Deploying enterprise applications across Azure environments (Dev, Test, and Production), including CI/CD pipelines, Infrastructure as Code (IaC), and release management practices

• Strong engineering ability in: Python, C#, TypeScript, or equivalent languages.
• Proven experience developing agentic AI workflows using Semantic Kernel, Assistants API, LangChain, LlamaIndex, or similar frameworks.
• Experience using AI-powered software engineering tools such as Claude Code or OpenAI Codex, owning and applying sound engineering judgement to all AI-generated code shipped to production.
• Integration development experience with enterprise platforms (SAP, ServiceNow, HRIS, or mining systems).
• Experience applying an AI-powered Test Driven Development (TDD) approach
• Hands-on experience with application monitoring and observability in production environments, including LLMOps and MLOps practices
• Proven experience evaluating LLMs and ML models, including designing evaluation frameworks for production use cases.
• Ability to follow established engineering standards and contribute to governance processes.
• Good communication skills with the ability to work effectively across technical and business teams.

Desirable

• Azure AI Engineer, Azure Developer, or Data Engineer certifications.
• Experience with MLOps platforms (Azure ML).
• Experience in mining, resources, or operational/asset-intensive industries.
• Familiarity with TOGAF, Agile, or equivalent architecture frameworks.

Key Outcomes in First 12 Months

• Actively contribute to the AI Center of Excellence through technical input, pattern development, and solution delivery.
• Build and deliver reusable AI components and agentic workflow solutions.
• Deliver multiple high-value AI initiatives into production with hands-on contribution.
• Build and maintain integrations across SAP, ServiceNow, Minestar, Ariba, and Azure using established patterns.
• Contribute to team knowledge sharing through documentation, patterns, and reusable components.
• Deliver consistent, secure, high-quality AI solutions aligned to the enterprise strategy.

Role Competencies

• Hands-On Engineering: Gets stuck into the technical work and delivers quality results.
• Solution Awareness: Understands how solutions fit within the broader enterprise context.
• Collaboration & Standards: Works effectively across teams and follows established technical standards.
• Technical Mastery: Strong skills across AI, cloud, integration, and engineering.
• Clear Communication: Able to simplify and present complex concepts clearly.
• Delivery Excellence: Focuses on practical delivery and getting things done at speed.

Why Join Us? 

• Opportunity to shape the future of mining through cutting-edge data solutions. 
• Collaborative and inclusive work environment. 
• Competitive compensation and benefits package. 
• Commitment to professional growth and sustainability initiatives.