Hybrid AWS DevOps Engineer – AI & Data Science
DFP Recruitment is hiring a contract AWS DevOps Engineer to build, automate, deploy and operate cloud infrastructure for AI/ML and data science workloads in an Australian Federal Government environment. Core stack: AWS, Terraform/CDK/CloudFormation, CI/CD, Docker/Kubernetes/EKS, plus security, monitoring and MLOps support. Hybrid across Sydney and Melbourne, 12-month contract, Australian citizens
- Compensation
- Not disclosed
- Location
- Melbourne, Australia
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Contract
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Must have
- Australian Citizens only
- Build AWS cloud infrastructure for ML workloads
- Infrastructure as Code with Terraform, AWS CDK, CloudFormation
- Build and maintain CI/CD pipelines
- Experience with Docker, Kubernetes and EKS
- Security and monitoring practices
- MLOps support for AI/data science solutions
Full description
DevOps Engineer – AI & Data Science12-month contractSydney and Melbourne location | Hybrid work arrangementsAustralian Citizens onlyDFP Recruitment is seeking an experienced DevOps Engineer – AI & Data Science to support the design, automation, deployment and ongoing operation of cloud infrastructure and engineering platforms supporting AI, machine learning, data science and software solutions within a Federal Government environment.This is an exciting opportunity to work within multidisciplinary teams delivering modern digital solutions, including generative AI, machine learning, Retrieval-Augmented Generation (RAG), automation and analytical applications.
Responsibilities**
- Design, build and maintain AWS cloud infrastructure supporting AI, machine learning and data science workloads.
- Develop and maintain Infrastructure as Code (IaC) using Terraform, AWS CDK, CloudFormation or equivalent.
- Design and maintain CI/CD pipelines for automated build, testing, security scanning and deployment.
- Deploy and support applications using Docker, Kubernetes and Amazon EKS.
- Manage cloud environments across development, testing, pilot and production.
- Support cloud networking, IAM, storage, compute and security services.
- Implement monitoring, logging, alerting and observability solutions.
- Troubleshoot complex infrastructure, deployment and operational issues.
- Support security controls, identity and access management, secrets management and vulnerability remediation.
- Support the deployment and operational management of AI, machine learning and generative AI solutions.
- Contribute to MLOps and LLMOps capabilities, including model deployment, monitoring and lifecycle management.
- Work with multidisciplinary teams including Data Scientists, AI Engineers, Machine Learning Engineers and Software Engineers.
- Develop technical documentation, operational runbooks and engineering standards.
- Contribute to continuous improvement, platform reliability, scalability and cost optimisation.
Essential criteria
- Strong experience designing, deploying and supporting AWS cloud-based solutions.
- Experience developing and maintaining CI/CD pipelines for reliable application and service deployment.
- Experience implementing Infrastructure as Code, using Terraform, AWS CDK, CloudFormation or equivalent.
- Experience with Docker and Kubernetes, preferably Amazon EKS.
- Experience implementing monitoring, logging and observability solutions.
- Demonstrated ability to troubleshoot complex infrastructure, deployment and operational issues.
Desirable skills
- Experience supporting AI, machine learning or data science platforms.