AI Automation Developer

•   Design, develop, and maintain AI-powered automation solutions using Microsoft Power Platform tools such as Power Automate, Power Apps, and Copilot Studio.
• Build and deploy intelligent agents using Agentic AI principles, enabling autonomous task execution and decision-making within enterprise workflows.
• Collaborate with data scientists, solution architects, and business stakeholders to integrate AI models and LLMs into business processes.
• Develop and manage CI/CD pipelines for AI and automation components using Azure DevOps, GitHub Actions, or similar tools.
• Create and maintain reusable components, connectors, and templates to accelerate automation delivery across teams.
• Ensure scalability, security, and compliance of AI automation solutions, leveraging Azure services like Azure Functions, Logic Apps, and Azure Machine Learning.
• Monitor and optimize performance of deployed AI agents and automation workflows, implementing logging, alerting, and diagnostics using Azure Monitor and Application Insights.
• Stay current with advancements in AI, LLMs, and Power Platform capabilities, and proactively recommend improvements or new use cases.
• Document solution architecture, workflows, and best practices to support knowledge sharing and operational continuity.
• Design and implement end-to-end Software Development Life Cycle (SDLC) best practices for AI and automation projects, utilizing Power Platform deployment pipelines to streamline the promotion of solutions from development through testing to production environments.
• Ensure robust change management, version control, and automated deployments to support reliable, scalable, and efficient delivery of Power Platform solutions.
• Microsoft Ecosystem Depth, Relevant Microsoft certifications (Power Platform, Azure AI), SharePoint and Teams integration experience, Microsoft Graph API experience.

About you:

• Experience with Agentic AI design patterns, including autonomous agents, task orchestration, and memory management within enterprise environments.
• Familiarity with Azure OpenAI Service and integrating LLMs into business workflows.
• Knowledge of advanced Power Platform capabilities such as custom connectors, Dataverse, and AI Builder.
• Experience with orchestration tools like Azure Data Factory, MLflow , or Kubeflow.
• Exposure to monitoring and observability tools (e.g., Application Insights, Azure Monitor).