GenAI Engineer

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.