Overview:

We are a global energy company based in Portugal, known for its strong commitment to sustainability and innovation. As a leader in renewable energy, we focus on clean electricity generation through wind, solar, and hydro power.

What are we looking for?

• Proven experience in Machine Learning, Generative AI, or related fields;
• Experience in data modeling and AI pipeline development;
• Proficiency with cloud solutions (Azure, AWS, Google Cloud);
• Ability to collaborate on global projects and work in distributed teams;
• Programming: Strong proficiency in Python and experience with relevant libraries;
• Experience using Azure AI Services for TTS  (eg ElevenLabs), STT (Whisper-large-v3), STS (gpt-4o-mini-realtime-preview, Azure Document Intelligence for OCR and Embeddings (text-embedding-3-small  and/or text-embedding-3-large);
• Deep understanding of Retrieval Augmented Generation (RAG) architecture and principles;
• Hands-on experience with LLM orchestration frameworks, specifically LangChain and LangGraph;
• Backend API development using FastAPI;
• Knowledge of Guardrails for content safety and LangFuse for observability, evaluation and feedback;
• Define and optimize generative AI models for different business scenarios;
• Train and validate GenAI models, ensuring strong performance;
• Implement GenAI solutions on cloud platforms, ensuring their efficiency;
• Contribute to the continuous improvement of analytical processes through the integration of GenAI;
• Autonomous development of applications based on Generative AI (OpenAI, AI Search);
• Autonomous development of Copilot solutions (Microsoft).

Generative AI & LLMs:

• Demonstrable experience building applications with Large Language Models on Microsoft Azure ecosystem, namely gpt-4o and o3;
• Knowledge of Gemini 2.5 Pro and Claude 3.7 Sonnet a plus.

Microsoft Azure Cloud:

• Proven experience developing and deploying applications on Azure;
• Azure Functions and Logic Apps: Experience building serverless applications;
• Azure OpenAI Service: Experience with deploying and using models like GPT-4 and text embedding models;
• Azure AI Search / AI Foundry: Knowledge of creating and managing vector stores for similarity search;
• Data Factory and Databricks for ingestion pipelines;
• Azure Blob Storage: Familiarity with cloud storage solutions;
• CosmosDB: Knowledge of creating and managing long-term memory;
• Application Insights: Knowledge of logging.

DevOps & MLOps:

• Proficiency with Docker for containerizing applications, Azure Container Registry as a plus;
• Experience deploying applications to multiple environments (e.g., dev, production) on Azure;
• Familiarity with CI/CD principles and scripting for automation, namely GitHub Actions;
• Secrets management using Azure Key Vault, GitHub and HashiCorp Vault.

AI Foundry knowledge in creating Copilots with GenAI capabilities (Microsoft Copilot Studio Framework):

• Creating pluggable grounding: configuring how the Copilot fetches external data;
• Setting up Retrieval Augmented Generation (RAG);
• Working with Azure OpenAI, Azure Cognitive Search, and vector search;
• Designing structured, custom prompts;
• Implementing plugins, external functions, and API integrations;
• Applying guardrails, safety filters, and validation logic.

Microsoft 365 (M365) Integration:

• Knowledge in Integration with Microsoft Graph API: Reading emails, calendars, OneDrive/SharePoint files, Teams meetings, etc.;
• Knowledge using M365 connectors in Power Automate to retrieve calendar events, schedule meetings, send Teams messages;
• Microsoft Entra ID (Azure AD) permissions;
• Graph Explorer/Postman for testing permissions and endpoints;
• Understanding M365 licensing and API usage limits.

Power Platform:

• Power Automate: building workflows triggered by Copilot interactions;
• Dataverse: structured data storage and retrieval;
• Power Fx: using formulas for basic business logic;
• Power Apps (basic): for integrating with custom apps.

Conversational Logic:

• Designing topics and triggers;
• Creating conditional flows with variables;
• Using session variables and maintaining context across interactions.

API and External Services Integration:

• Making REST API calls via custom connectors or Power Automate;
• Knowledge of OAuth 2.0, Azure AD, and token-based authentication.