Software Developer (AI DevOps Engineer)

• The role focuses on delivering scalable automation and DevOps solutions using Microsoft Power Platform, Azure services, and scripting technologies.
• Accountabilities
• Develop and maintain automation solutions using Microsoft Power Platform, including Power Apps and Power Automate.
• Develop and enhance scripts using PowerShell and Python to support infrastructure and business process automation.
• Build and maintain DevOps pipelines supporting CI/CD and automated deployment processes.
• Develop integrations between business applications and cloud platforms using REST APIs.
• Support the implementation of AI-driven solutions using Copilot Studio and Azure AI technologies.
• Work collaboratively with product owners, developers, and operations teams to deliver automation initiatives.
• Participate in agile ceremonies including sprint planning, backlog refinement, daily stand-ups, and retrospectives.
• Troubleshoot application and automation issues, identify root causes, and implement corrective actions.
• Maintain technical documentation for automation workflows, integrations, and deployment processes.
• Ensure solutions comply with Computacenter governance, security, and operational standards.

Knowledge & Key Skills

Essential

• Experience with Microsoft Power Platform (Power Apps and Power Automate).
• Strong understanding of Azure cloud services and DevOps practices.
• Proficiency in PowerShell and/or Python scripting.
• Understanding of Agile development methodologies.
• Experience designing and consuming REST APIs.
• Strong analytical and problem-solving skills.
• Ability to work effectively within cross-functional teams.
• Good communication and documentation skills.

Desirable

• Experience with Rundeck job orchestration.
• Exposure to Azure AI and Copilot Studio.
• Experience with Ansible automation.
• Understanding of cloud-native automation patterns.
• Knowledge of enterprise integration practices.

Critical Success Factors

• Delivery of reliable and scalable automation solutions.
• Successful implementation of AI-enabled automation capabilities.
• Reduction of manual effort through effective automation initiatives.
• Strong collaboration across engineering and business teams.
• Compliance with organizational governance and security standards.