Andrew Shaw

Senior DevOps Engineer

Highly skilled and experienced DevOps engineer and Agile consultant with a strong background in cloud infrastructure, automation, and security. Proven ability to design, implement, and maintain secure, reliable, and scalable cloud solutions. Expertise in AWS, Terraform, Ansible, and other DevOps tools. Experienced in security hardening and ensuring compliance with industry best practices.

Experience

Conditioning Shed Worker

Hop Products Australia | 2025
  • Scanning, temperature checking and stacking of hop bales
  • Warehouse management using pallets lifts and forklifts

Software Engineer

CultureAmp | 2022
  • Developed and maintained cloud infrastructure on AWS using Terraform, Docker, and Buildkite.
  • Implemented and automated security hardening measures.
  • Worked with Python to automate tasks and improve efficiency.

Site Reliability Engineer

Latitude Financial | 2021
  • Managed and monitored AWS infrastructure, ensuring high availability and reliability.
  • Utilized Datadog and Sumologic for monitoring and log management.
  • Automated infrastructure provisioning and configuration using Terraform and Docker.

Software Engineer

CarNextDoor | 2018 - 2020
  • Developed and deployed applications on AWS using Ruby on Rails, Javascript, and Docker.
  • Contributed to the design and implementation of secure cloud infrastructure.

DevOps Consultant

Cevo Australia | 2015 - 2018
  • While working for Cevo I had the opportunity to advise and assist numerous clients in solving particular DevOps challenges, such as migrations to the cloud, automated testing and security auditing, and cost saving, to name a few. This has given me experience in using a wide range of technologies, particularly AWS, Chef, Ansible, Terraform, and Docker

Consultant

Thoughtworks | 2012 - 2015
  • Consulting with clients on cloud infrastructure, DevOps best practices, and security. Primarily working with AWS, Azure, and VMWare to design and implement cloud solutions.

Simulation Analyst

Defence Science and Technology | 2010 - 2012
  • Developing simulations of defence training and procurement to predict future readiness for national security requirements.

Projects

Spatial AI

A project spanning infrastructure, robotics, computer vision and LLM AI, this is an ongoing effort to analyse data from real world sensors such as depth cameras and LIDAR scanners using an iterative approach combining image classification techniques such as YOLO with the more recent Large Language models to build AIs with spatial awareness and ability to reason about 3D environments

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