Lead the design, implementation, and management of Azure DevOps pipelines and infrastructure.
Develop and maintain CI/CD pipelines to automate the build, test, and deployment processes.
Collaborate with development, QA, and operations teams to ensure seamless integration and delivery of software solutions.
Implement and manage infrastructure as code (IaC) using tools such as ARM templates, Terraform, or Bicep.
Monitor and optimize the performance, scalability, and reliability of our cloud infrastructure.
Ensure security best practices are followed in all DevOps processes and tools.
Provide technical leadership and mentorship to junior DevOps engineers.
Stay up to date with the latest industry trends and best practices in DevOps, AI and cloud technologies.
Proven experience with Azure DevOps, including Boards, Repos, Pipelines, and Artifacts.
Strong scripting capabilities in PowerShell, Bash, or Python.
Practical experience designing and implementing CI/CD workflows using GitHub Actions and GitLab Pipelines, including automation, testing, and deployment best practices.
Experience with modern programming languages such as Java, C#, JavaScript, Python, Go, or Ruby, alongside scripting languages.
Hands-on experience with Infrastructure as Code (IaC) and automation tools like Bicep and Terraform, enabling the creation and maintenance of complex cloud environments.
Solid understanding of cloud service models including PaaS, Serverless, and IaaS (e.g., VMs, storage), with a focus on secure configuration and DevSecOps principles.
Familiarity with AI-enhanced DevOps practices, including how AI can improve CI/CD, observability, testing, and infrastructure automation.
Ability to ensure AI tools comply with enterprise-grade security, privacy, and governance standards.
Experience with source control systems such as GitHub and Azure DevOps
Working knowledge of Azure services including Application Insights, Azure DevTest Labs, API Management, Web and Mobile Apps, and Windows VMs.
Practical experience with containerisation technologies like Docker and Kubernetes, and cloud-native architecture patterns.
Familiarity with monitoring and observability tools such as Azure Monitor, App Insights, Prometheus, and Grafana.
Demonstrated ability to implement and manage GitOps workflows, using Git as the single source of truth for infrastructure and application configurations, and enabling continuous delivery through automated CI/CD pipelines.
Ability to identify and integrate AI-driven tools into existing DevOps workflows to enhance efficiency and resilience.
Awareness of security and compliance frameworks such as ISO 27001, SOC 2, and related standards.
Azure certifications such as AZ-400: Designing and Implementing Microsoft DevOps Solutions)
AI-related certifications (e.g., AI-102 Azure AI Engineer Associate) are advantageous.
Knowledge of security best practices in cloud environments such as Certified Cloud Security Professional (CCSP) or Azure Security Engineer Associate (AZ-500)
GitOps Certified Associate (CGOA)