Data & AI Engineer
Apply for this job
These roles are hiring now
View all AI roles →Senior Machine Learning Engineer
- Design, build and optimise ML infrastructure and data science workflows
- Production ML systems experience required
- Python, scikit-learn, PyTorch, TensorFlow, GCP, FastAPI, Docker, K8s
Senior Engineering Manager - Data & AI
- Lead multi-disciplinary teams building scalable AI/ML & data solutions
- 2+ years managing multi-disciplinary engineering teams
- Python, ML frameworks, cloud platforms, DevOps/MLOps, GenAI
Cyber Resilience and Reliability Lead (IC)
- Strengthen cyber security resilience and drive technology optimisation
- Senior/Principal level experience in cyber security engineering
- Cyber security technologies, AI-driven security, stakeholder management
AI Deployment Engineer, Startups
- Work with strategic startups on AI deployment, optimization and evaluation
- Software engineering, ML engineering or Data Science experience
- AI applications, agents, evaluation systems, prompt engineering
Brunel has partnered with an Energy & Resources industry leader to offer an exciting contract opportunity for an AI Engineer. This role is well suited to someone with strong software and ML engineering experience, who is looking to deepen their expertise across ML, GenAI, and MLOps platforms.
The Data & AI Platform team builds the foundational capabilities that enable scalable, secure, and high-impact AI solutions. We design and operate the platforms, components, and workflows that support machine learning, GenAI, data-driven optimisation, and enterprise automation.
As an AI Engineer / Developer, you will help build and operate our AI platform-supporting traditional ML, LLM-based applications, orchestration frameworks, and end-to-end MLOps/LLM Ops processes. You'll work with data scientists, architects, and product teams to deliver reliable, integrated, and value-focused AI solutions across the business.
Key Responsibilities
AI Platform Engineering and Development
- Develop and maintain reusable AI components, APIs, microservices, and orchestration frameworks.
- Support the implementation of ML and GenAI architectures, including retrieval pipelines and agentic workflows.
- Build platform capabilities for model deployment, automation, monitoring, evaluation, and lifecycle management (MLOps & LLM Ops).
Enterprise Solution Integration
- Integrate AI services into business workflows, ensuring alignment with enterprise architecture, security, and data governance.
- Collaborate with cross-functional teams to deliver scalable and production-ready AI solutions.
- Contribute to prototyping and experimentation to validate technical feasibility and operational value.
Collaboration and Communication
- Explore emerging AI/ML and GenAI technologies and assess their applicability within the business.
- Document platform patterns, best practices, and operational procedures.
- Participate actively in knowledge sharing, capability uplift, and continuous improvement activities.
- Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, or related field.
- Minimum 2+ years of experience in designing, developing and delivering AI/ML systems, including cloud-native solutions.
- Required Skills
- Software Engineering/Programming: Proficient in Python (essential). Familiarity with TypeScript/JavaScript, C#, or Go beneficial.
- ML/AI Frameworks: Practical experience with ML frameworks such as PyTorch, TensorFlow, Hugging Face, and LangChain.
- GenAI & RAG: Exposure to embedding models, vector stores, retrieval chains, and agentic orchestration approaches is desirable.
- Cloud & DevOps: Working knowledge of cloud platforms (AWS or Azure), containerization (Docker), orchestration (Kubernetes), infrastructure-as-code (Terraform), and familiarity with CI/CD processes and monitoring tools.
- Data & Platform Engineering: Basic experience or familiarity with tools and services such as Snowflake, Kafka, AWS S3, REST APIs, microservices architecture, and knowledge graph integration beneficial.
- Desirable Skills
- Experience in industrial automation, heavy industry, or operational technology environments.
- Experience with OpenAI integrations, SageMaker, or Databricks.
- Knowledge of AI governance, security, and ethical deployment of AI systems.
About Brunel:
Brunel is a recruitment and flexible workforce solution provider which connects talented people with opportunities throughout Australasia and around the world. We specialise in highly skilled roles across a variety of technical, professional, trades and craft disciplines, pairing candidates with industry-leading projects and organisations on a contract, permanent or secondment basis.
Operating in Australasia since 1997, Brunel has major bases of operation in Perth, Sydney, Brisbane and Port Moresby, which are further backed by the strength and reach of a truly global network spanning over 45 countries, 120 offices and 45 years of successful operation.
Brunel is proud to be equal opportunity employer and encourages applications from Aboriginal and Torres Strait Islander and female candidates.
#LI-JG1
How to apply:
If you meet the above requirements and would like to be considered for this role, please submit your interest using the 'Apply' button. Applying is quick and easy - just make sure you have the following documents ready to go:
- Resume
- Cover Letter (optional)