Portfolio

12+ Years of Delivery

Enterprise software across five industries — the breadth of experience that makes AI consulting effective.

6+

Energy & Utilities

6

Transport & Government

2+

Telecommunications

2

IoT & Research

2

Education

Energy

Energy Trading Platform

CleancoQLD · 2020 – 2026

TypeScriptReactAzureNode.jsCosmosDBEvent-Driven

Led development of mission-critical energy trading systems for Queensland's government-owned clean energy generator. Built the applications that CleancoQLD's traders use to buy and sell power on the AEMO energy market, processing real-time market data with zero margin for error.

  • Event-driven architecture handling real-time AEMO market data
  • Trader-managed automation system for energy dispatch
  • 99.99% uptime across production systems
  • Azure Functions, CosmosDB, Service Bus, Event Grid
  • Built entire development capability from zero — Git workflows, CI/CD, cloud infrastructure
  • Consistent fortnightly deployments through automated pipelines

Why this matters for AI:

The same event-driven, real-time patterns that power energy trading are exactly what AI-augmented systems need — handling data streams, making decisions under constraints, and operating with zero tolerance for failure.

Energy

Retail & Wholesale Deal Capture

CleancoQLD · 2020 – 2026

TypeScriptReactAzure Data FactoryREST APIs

Built two applications for capturing energy deals across retail and wholesale markets, enabling accurate market position calculations and supporting risk and analytics teams.

  • Integrated with multiple upstream data sources and downstream reporting systems
  • Automated data pipelines using Azure Data Factory
  • Supported risk and analytics teams with real-time position data
  • Deprecated legacy .NET applications, migrating to modern TypeScript/React stack

Why this matters for AI:

Data integration and pipeline automation are core to any AI initiative. Connecting multiple data sources into a unified system is the foundation of effective AI deployment.

Transport & Government

Intelligent Transport Systems

Transmax / DTMR · 2016 – 2020

ReactVue.js.NET CoreNode.jsAWSDocker

Built and deployed real-time traffic management systems used across Queensland and internationally. Led a team of three developers building cloud and web applications for Queensland's Intelligent Transport Systems.

  • First international deployment — Colorado DOT pilot program
  • Real-time traffic management dashboards
  • AWS Lambda, EC2, and serverless architecture
  • First fully automated build and deployment pipeline at Transmax

Why this matters for AI:

Transport systems taught me how to integrate new technology into existing infrastructure without disruption — the exact challenge businesses face when adopting AI.

Transport & Government

STREAMS ITS Platform

Transmax · 2014 – 2016

C#.NETAWSMongoDBRedisElasticsearch

Developed and maintained Transmax's flagship ITS integration platform — enterprise-scale traffic management software used across Queensland's road network.

  • Led migration of large coupled codebase to modern AWS-hosted architecture
  • Reduced server provisioning time from hours to minutes using Chef and Packer
  • Built backend services with .NET Web API, MongoDB, Redis, and Elasticsearch
  • Completed 3-month secondment as Business Analyst

Why this matters for AI:

Legacy modernisation experience is directly applicable to businesses looking to add AI to existing systems — understanding how to evolve complex platforms without breaking them.

Telecommunications

CRM Integration & Business Automation

Moose Mobile · 2012 – 2014

C#.NETPHPJavaScriptSQL ServerHardware

Built custom CRM plugins, internal tools, and business automation for a growing Australian mobile virtual network operator (MVNO).

  • Custom Act! CRM plugins and integrations using C#/.NET
  • Built GSM gateway prototype using Raspberry Pi — significantly reduced call costs
  • Coordinated with offshore development teams
  • Full-stack web development with PHP, JavaScript, and SQL Server

Why this matters for AI:

Small business automation at its core — the same mindset applies to AI: find the repetitive, costly process and build a better solution.

IoT & Research

IoT Wildlife Research Platform

QUT Bioacoustics Research · 2013 – 2014

C#.NETIoTATMELData AnalysisHardware

Built data analysis tools and hardware for a research project analysing male koala bellows via smart sensors, collaborating with QUT's Bioacoustics Research Team and UQ's Koala Ecology Group.

  • C#/.NET data analysis tools for acoustic sensor data
  • Hardware development using ATMEL microprocessors
  • Cross-disciplinary collaboration with ecology researchers
  • Full-scholarship Master's research

Why this matters for AI:

IoT and sensor data analysis is a growing AI application area. This early experience with data pipelines from physical sensors to analysis software mirrors modern AI data ingestion patterns.

Certifications

Continuous Learning

Actively pursuing industry certifications to complement hands-on experience with formal validation.

Azure AI Fundamentals

AI-900

In Progress

Azure AI Engineer Associate

AI-102

Planned

AWS AI Practitioner

AIF-C02

Planned

Want this experience applied to your business?

Let's discuss how 12+ years of enterprise delivery can accelerate your AI initiative.