Date: 13 Nov 2026
Location:
Brisbane, QLD, AU
Department: Technology & Transformation
Description:
Job Requisition ID: 41821
Senior GCP AI/ML Engineer
Design, develop and deploy AI/ ML, and intelligent agent solutions on Google Cloud Platform (GCP).
Build production-ready solutions using Google Cloud Gemini Enterprise Agent Platform (Vertex AI), Python / R and cloud-native data and application services.
Turn complex data and emerging AI capabilities into scalable solutions that improve client outcomes.
About the GCP AI/ML Engineer role
Based in Brisbane/Canberra/Melbourne/Sydney, you will join our AI & Data practice and work across the full AI and machine learning lifecycle, from opportunity identification and solution design through to deployment, monitoring and continuous improvement. You will use Google Cloud technologies, including Vertex AI and Gemini, to build practical, secure and scalable solutions for complex client environments.
What will your typical day look like?
You will collaborate with data scientists, data engineers, architects, product teams and business stakeholders to identify valuable AI and ML opportunities and translate them into production-ready solutions. Your work may include preparing data, developing models and algorithms, building AI model, training models, monitoring performance and communicating technical decisions to stakeholders.
You will be responsible for:
Design, develop, train, test and deploy AI/ML solutions on GCP.
Develop BigQuery and BigQuery ML, Auto ML, custom models, algorithms and data features using Python / R and relevant machine learning libraries.
Use Google Cloud Gemini Enterprise Agent Platform (Vertex AI) for model development, training, evaluation, deployment and monitoring.
Apply various modelling methods and advanced analytics to improve customer, operational and business outcomes.
Translate business needs into clear technical designs, delivery plans and measurable outcomes.
Apply prompt engineering, grounding, evaluation and guardrail techniques to improve solution quality and reliability.
Experiment with emerging AI capabilities and Agentic AI exposure to convert viable prototypes into reusable, production-ready assets.
Build/Support automated deployment, testing and monitoring practices for AI and ML solutions.
Monitor model performance, data drift, quality, cost and operational outcomes, and implement continuous improvements.
Communicate technical concepts, risks and recommendations clearly to technical and non-technical stakeholders.
How this role brings our table-stakes behaviours to life
Our core behaviours guide how we work: Be Curious, Reuse and Improve, Validate and Elevate, Reinvent Delivery, and Show, Don't Tell. In this role, you will explore emerging AI and ML techniques, build working solutions, validate outcomes with evidence, reuse proven patterns and help teams deliver measurable client value.
About the team
Our AI & Data team br ings together specialists across Australia who combine deep technical expertise with strong business insight. We work with public and private sector clients to design and implement advanced analytics, cloud data, machine learning and Generative AI solutions. You will work alongside AI engineers, data scientists, data engineers, architects and client teams, with access to Deloitte's broader alliance ecosystem and delivery capabilities.
Enough about us, let’s talk about you.
We are seeking an experienced, hands-on GCP AI/ML Engineer who can take ownership of technical outcomes while working effectively with clients and multidisciplinary teams.
Minimum 10 years’ relevant experience across AI, machine learning, data science, data engineering or software engineering, including demonstrable hands-on delivery.
Hands-on 5+ years of experience designing and delivering AI/ML solutions on Google Cloud Platform.
Strong experience with Vertex AI (Gemini Enterprise Agent Platform) model development and deployment, including Generative AI capabilities and Gemini models.
Strong programming capability in Python/R and experience with common machine learning and data science libraries.
Practical knowledge of machine learning techniques, predictive modelling, deep learning, neural networks, chatbots or image processing.
Experience building production-ready cloud application and model pipelines.
Understanding of MLOps, model evaluation, monitoring, security, privacy and responsible AI practices.
Ability to design end-to-end solutions and clearly articulate architecture, delivery approach, dependencies and risks.
Strong written and verbal communication skills, with confidence engaging both technical and non-technical stakeholders.
Strong problem-solving skills and the ability to deliver in a flexible, fast-paced environment.
A bachelor's or master's degree in computer science, engineering, data science or a related field is desirable.
Google Cloud Professional Machine Learning Engineer certification is highly desirable.
Australian Citizenship with baseline clearance is mandetory.
By applying for this job, you’ll be assessed against the Deloitte Talent Standards. We’ve designed these standards so that you can grow in your career, and we can provide our clients with a consistent and exceptional Deloitte employee experience globally. The preferred candidate will be subject to background screening by Deloitte or by their external third-party provider.
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