Accountabilities:

Design, develop, implement, integrate, and maintain AI agents using Microsoft 365 Copilot, Microsoft Copilot Studio, and Azure AI Foundry.
Build intelligent workflows and business process automations using Power Automate, Power Apps, and Power Pages.
Develop integrations with Microsoft Teams, SharePoint, Outlook, OneDrive, Microsoft Graph API, and other enterprise applications.
Leverage Microsoft Fabric to integrate, transform, organize, and make corporate data accessible to AI agents.
Develop and manage data ingestion and transformation pipelines using Microsoft Fabric Data Factory, Dataflows Gen2, OneLake, Lakehouse, and Warehouse.
Implement Generative AI solutions using Azure OpenAI Service, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) techniques.
Integrate AI agents with REST APIs, relational and non-relational databases, corporate systems, and enterprise knowledge bases.
Implement authentication and authorization mechanisms using Microsoft Entra ID, ensuring secure access to enterprise resources.
Contribute to the architecture and development of intelligent agents, including multi-agent systems, context management, and conversational memory.
Apply security, governance, observability, and monitoring practices throughout the AI solution lifecycle.
Conduct functional and technical testing, validate agent performance, and evaluate the quality, reliability, and security of AI-generated responses.
Create and maintain functional, technical, and architectural documentation, including testing and validation evidence.
Manage version control, deployment, continuous integration, and delivery processes using CI/CD practices.
Ensure the delivery of reliable, scalable, secure, and fully integrated AI agents within the corporate environment.

Requirements

Microsoft Ecosystem: Practical experience with Microsoft 365 Copilot, Microsoft Copilot Studio, Power Automate, Power Apps, Power Pages, Dataverse, Microsoft Teams, SharePoint Online, and Microsoft Graph API. Familiarity with Azure AI Foundry, Azure OpenAI Service, Azure Functions, Azure Logic Apps, Microsoft Entra ID, and Azure DevOps or GitHub.
Microsoft Fabric and Data Engineering: Knowledge of Microsoft Fabric and its core components, including OneLake, Lakehouse, and Warehouse. Experience with Data Factory, data ingestion and transformation pipelines, and Dataflows Gen2. Understanding of SQL, data modeling, and integration between Microsoft Fabric, Dataverse, SharePoint, and Azure. Ability to prepare and expose structured enterprise data for AI agent consumption, with an understanding of data governance, security, and access control.
Development and Integration: Knowledge of at least one programming language, such as Python, C#/.NET, or TypeScript/JavaScript. Experience developing and consuming REST APIs, with familiarity with JSON, OAuth 2.0, token-based authentication, service-oriented and event-driven architectures, relational and non-relational databases, Git, and CI/CD practices.
Generative Artificial Intelligence: Understanding of Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), Tool Calling, and Function Calling. Knowledge of intelligent agent orchestration, multi-agent architectures, enterprise knowledge base integration, context management, conversational memory, and techniques for evaluating the quality and security of AI-generated responses.
Nice to Have: Familiarity with Microsoft Agent Framework, Semantic Kernel, Model Context Protocol (MCP), Azure AI Search, PySpark, Microsoft Fabric notebooks, Data Lake and Lakehouse architectures, Azure API Management, and custom connector development. Hands-on experience with multi-agent solutions, AI observability and monitoring, information security, data governance, and Brazil's LGPD requirements. Microsoft certifications in Artificial Intelligence, Power Platform, Azure, or Microsoft Fabric are also an advantage.
Soft Skills: Strong analytical thinking and problem-solving abilities, technical autonomy, and a proactive approach. Ability to understand the relationship between business processes, applications, and data. Excellent communication skills when working with technical teams and business stakeholders, combined with a collaborative mindset, adaptability, curiosity for innovation, and commitment to quality and development best practices.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

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