AI Engineer

As an AI Engineer at ITxend, you will work at the intersection of cutting-edge AI research and real-world enterprise deployment. You will collaborate with cross-functional teams to understand business problems, architect AI solutions, and ensure they are robust, scalable, and maintainable in production. You will have the opportunity to work with the latest LLM frameworks, cloud-native AI services, and MLOps tooling — making a direct impact on some of Portugal's most demanding technology environments.

• Design and implement end-to-end AI/ML pipelines for enterprise clients, from data ingestion to model serving.
• Develop and fine-tune large language models (LLMs) and generative AI solutions using Azure OpenAI, AWS Bedrock, and open-source frameworks.
• Build robust MLOps infrastructure including model versioning, monitoring, and automated retraining pipelines.
• Collaborate with data engineers to ensure high-quality, well-structured data pipelines feeding AI models.
• Conduct code reviews, establish best practices, and mentor junior engineers on the team.
• Communicate technical findings and model performance to non-technical stakeholders and clients.
• Stay current with AI/ML research and evaluate emerging tools and frameworks for potential adoption.

• 5+ years of professional experience in software engineering, with at least 3 years focused on ML/AI systems.
• Strong proficiency in Python and the modern ML ecosystem (PyTorch, TensorFlow, HuggingFace, LangChain).
• Hands-on experience deploying and fine-tuning LLMs in production environments.
• Solid understanding of MLOps practices: CI/CD for ML, model monitoring, feature stores, and experiment tracking (MLflow, Weights & Biases).
• Experience with cloud-native AI services: Azure OpenAI, AWS Bedrock, or Google Vertex AI.
• Proficiency with containerisation (Docker, Kubernetes) and infrastructure-as-code (Terraform).
• Strong communication skills in English; Portuguese is a plus.

• Experience with RAG (Retrieval-Augmented Generation) architectures and vector databases (Pinecone, Weaviate, pgvector).
• Background in NLP, computer vision, or time-series forecasting for enterprise use cases.
• Contributions to open-source AI projects or published research.
• Experience working in regulated industries (finance, healthcare, critical infrastructure).