Top Artificial Intelligence Jobs in Portugal

Design, develop, and deploy production-ready AI solutions for insurance, focusing on agentic AI, multi-agent systems, LLMs, RAG pipelines, and computer vision. Research and implement state-of-the-art models, take prototypes through production, collaborate with data scientists and engineers, and contribute to proprietary insurance-focused AI models and scalable international AI products.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.

Design, build, and maintain scalable Java microservices (Java 17/21, Spring Boot). Architect agentic AI systems using Spring AI or LangChain4j, integrate Azure Copilot via REST APIs, craft and version-control prompts, implement reliability guardrails and observability, and collaborate with product, frontend, and mobile teams to deliver end-to-end AI features.

Design, develop and deploy machine learning and deep learning (including genAI) models to improve credit risk data quality. Perform EDA, feature engineering, model evaluation, automation, and collaborate with stakeholders to translate business needs into data-driven solutions while ensuring regulatory compliance and coordinating monitoring committees.

Build and test AI-agent features and internal agent frameworks for a proactive cybersecurity platform. Implement and integrate generative AI systems (agents and RAG), stay current with AI research, and apply innovations to product development and evaluation within a security-focused environment.

Design and implement generative AI and ML solutions, build multimodal agents and automated workflows, develop MLOps tooling and cloud deployment pipelines (Azure/AWS/GCP), use Python/Databricks/SQL/PySpark/Docker/LangGraph, document work and present results to stakeholders.

The role involves developing AI-driven solutions, integrating APIs, and designing scalable software systems while collaborating with a multidisciplinary team.

Design, build, evaluate, and deploy LLM-driven features and AI systems. Collaborate with engineering and product teams to implement RAG, monitoring, CI/CD, and scalable cloud ML deployments while continuously improving model performance.

As the AI Agents Solutions Architect at Kraken, you'll design and build an AI-native finance operating system, automating finance operations and ensuring compliance in a regulated environment.

The Principal AI Engineer will build and improve the core AI tutoring system, design evaluation methods, and collaborate on pedagogical goals, driving innovation in learner experiences.

Lead Oyster's data platform and AI strategy, centralize AI initiatives into production systems, build scalable data and MLOps infrastructure, modernize knowledge architecture and semantic search, partner cross-functionally to embed AI into products and workflows, enforce tooling standards and governance, and drive organizational adoption and change management for AI-assisted operations.

Build and evolve an AI tutoring system, run evaluations, design software, collaborate with teams, and ensure quality through testing and refinement.

Responsible for building and evolving an AI tutoring system, running experiments, collaborating with teams, and ensuring quality in model behaviors.

The Curriculum Manager will oversee the content development lifecycle, recruit instructors, design curriculum, assess course performance, and improve data science and engineering content.

As a Principal AI Engineer, you'll build and evolve AI tutoring systems, run experiments for learning effectiveness, design software, collaborate across teams, and prototype AI interactions.

As an AI Creative Producer, you'll develop and scale AI-generated content across various platforms, collaborate with teams, and enhance production workflows.

Build and maintain enterprise web applications using .NET and Angular, participate in full SDLC, integrate AI services and APIs, leverage AI-powered development tools and LLM/RAG solutions, contribute to architecture and technical decisions, collaborate with clients and delivery teams, and ensure compliance with enterprise/regulatory standards.

Build and productionize generative AI systems and ML pipelines for unstructured data (documents, transcripts, images). Develop APIs, retrieval/RAG workflows, embedding pipelines, and model monitoring. Collaborate with data scientists and engineers to deploy, monitor, and maintain scalable, secure AI services using cloud and MLOps practices.

We are seeking an experienced AI Engineer with a focus on Generative AI to develop scalable solutions. Responsibilities include AI development, programming in Python, LLM integration, and API integration.

The AI Infrastructure Engineer will build and manage scalable model serving infrastructure for AI/ML applications, ensuring high efficiency and reliability in production.

Lead the Portugal COE innovation roadmap: run workshops, mentor teams, prototype and build FOAK automations using Google Apps Script and LLM-assisted coding, and operationalize experiments into deployed, documented, billable solutions.

Lead product strategy and delivery for AI agent configuration and personalization features. Build admin and user-facing tools (personas, tone, permissions), collaborate with engineering and design, measure adoption and satisfaction, and iterate using customer discovery and data-driven validation.

The Business Development Rep will qualify clients and manage outreach in AI Cloud sales, engaging technical audiences and developing partnerships.

The Product Manager for AI Productivity will identify, prioritize, and implement AI-driven initiatives, focusing on improving operational efficiency at Salsify.

Design, build, and scale ETL/ELT and real-time data pipelines for AI workloads (RAG, fine-tuning, batch inference). Transform unstructured data into vectorized formats, manage feature stores and vector databases, enforce data quality/governance, integrate event systems (Kafka), and collaborate with ML and engineering teams.