GenAI ENGINEER MASTER (HYBRID)

GenAI ENGINEER MASTER (HYBRID)

Portuguese company hires for hybrid work

Working Model:Hybrid

Location: Lisbon Portugal (2/3 times per week in Client)

Language Requirements:Fluent Portuguese and English min B2

Seniority:10 Years

Instructions:Please send your CVs in English and make sure to include all skills and experience that match the requirements of the opportunity. This will significantly increase your chances of success.

We are seeking a talented and forward-thinking GenAI Engineer to lead the end-to-end development and deployment of cutting-edge generative AI solutions. This role covers the entire lifecycle of GenAI applicationsfrom concept and design to productionwhile driving innovation in AI strategy and advancing cloud-based infrastructures.

Key Deliverables

• Lead the full lifecycle of GenAI solutions from design to deployment.
• Develop and implement generative AI strategies for predictive and prescriptive applications.
• Identify and explore new opportunities to apply GenAI across diverse client use cases.
• Enhance cloud infrastructures with a strong focus on AI-driven capabilities.
• Independently design and build GenAI-based applications (e.g. OpenAI AI Search).

Must-Have Qualifications /must be clearly listed on your CV:

• Proven track record in Machine Learning Generative AI or related fields.
• Excellent communication and leadership skills with the ability to guide technical teams.
• Deep expertise in integrating GenAI with cloud infrastructures.
• Experience in designing and executing large-scale GenAI strategies.
• Programming: Advanced Python proficiency with relevant ML/AI libraries.

Generative AI & LLMs

• Hands-on experience building applications with Large Language Models on Microsoft Azure particularly GPT-4o and o3.
• Familiarity with Gemini 2.5 Pro and Claude 3.7 Sonnet is a plus.
• Experience using Azure AI Services for: TTS (e.g. ElevenLabs) STT (Whisper-large-v3) STS (gpt-4o-mini-realtime-preview) OCR & Embeddings (Azure Document Intelligence text-embedding-3-small/large)
• TTS (e.g. ElevenLabs)
• STT (Whisper-large-v3)
• STS (gpt-4o-mini-realtime-preview)
• OCR & Embeddings (Azure Document Intelligence text-embedding-3-small/large)
• Strong understanding of Retrieval-Augmented Generation (RAG) architecture.
• Proficiency in LLM orchestration frameworks (LangChain LangGraph).
• Backend API development using FastAPI.
• Knowledge of Guardrails for content safety and LangFuse for observability evaluation and feedback.

Microsoft Azure Cloud

• Proven experience designing developing and deploying applications on Azure.
• Azure Functions and Logic Apps for serverless architectures.
• Azure OpenAI Service for deploying LLMs and embeddings.
• Azure AI Search / AI Foundry for vector store and similarity search management.
• Azure Data Factory and Databricks for data ingestion pipelines.
• Azure Blob Storage for scalable cloud storage.
• CosmosDB for persistent long-term memory.
• Application Insights for monitoring and logging.

DevOps & MLOps

• Proficiency with Docker for containerization; Azure Container Registry is a plus.
• Multi-environment deployment (dev staging production).
• CI/CD automation with GitHub Actions.
• Secrets management using Azure Key Vault GitHub and HashiCorp Vault.

Top Skills

• Generative AI Strategy & Implementation
• Large Language Models (LLMs): GPT-4o Gemini 2.5 Pro Claude 3.7 Sonnet
• Retrieval-Augmented Generation (RAG)
• Azure AI Services: TTS STT STS OCR Embeddings
• LLM Orchestration: LangChain LangGraph
• Content Safety & Observability: Guardrails LangFuse
• Python (ML/AI Libraries)
• FastAPI Backend Development
• Autonomous GenAI Application Development
• Cloud-Native Application Architecture
• Azure OpenAI Service & AI Search / AI Foundry
• Azure Functions & Logic Apps
• Azure Data Factory & Databricks
• Azure Blob Storage & CosmosDB
• Application Insights & Logging
• Docker & Azure Container Registry
• CI/CD Automation (GitHub Actions)
• Secrets Management (Azure Key Vault GitHub HashiCorp Vault)
• Multi-Environment Deployment (Dev Prod)

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