Top Artificial Intelligence Jobs in Portugal

The AI Solutions Manager drives strategy and commercialization of AI solutions, focusing on scalable solutions, partnerships, and sales enablement.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

The Principal Product Designer will drive product design strategy, mentor other designers, and lead complex design initiatives while ensuring high-quality, user-centered design practices.

As a Curriculum Manager, you will manage content development for the data science and engineering curriculum, collaborating with instructors and teams to enhance learning experiences.

Manage curriculum development for data science and engineering, collaborate with instructors, create content, and drive improvements based on learner feedback.

The AI Creative Executor will lead AI-enabled marketing campaigns, blending storytelling with technology, managing end-to-end production and collaborating with the marketing team to ensure alignment with brand standards.

The role involves managing AI-powered application development for marketing, translating business needs into technical solutions, and collaborating with stakeholders on project execution, integration, and deployment.

The AI Motion Designer will create marketing videos using AI tools, producing and adapting content for various platforms, and managing the video production process from concept to delivery.

The Senior AI Engineer develops and maintains machine learning applications, focusing on NLP and statistical methods to enhance customer experience and innovate product offerings.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

Lead AI architecture and implementation for financial services clients: support business development, enable and manage engineering teams, design scalable LLM/multi-agent systems, ensure AI safety, compliance, and monitoring, and translate business needs into technical specifications.

The Quality Assurance Engineer will participate in Agile ceremonies, design automated tests with Python, apply AI-assisted techniques, and improve QA practices for optical networking solutions.

Lead AI transformation strategies for clients, conduct workshops, develop AI solutions, enhance internal AI literacy, advise on organizational change, and build partnerships in the AI ecosystem.

As a Full Stack Engineer, you'll design and deliver backend services, build AI agent tools, integrate APIs, and automate workflows, while ensuring operational excellence and CI/CD practices.

As a Senior AI Engineer, you will develop AI-powered features, integrating LLM APIs to enhance user workflows while collaborating with teams to ensure reliability and scalability.

The Product Owner for Payments & Finance will manage product initiatives, enhance financial workflows, and leverage AI for operational efficiency.

Lead product strategy and execution for AIVM's agentic AI and blockchain platform, ensuring technical alignment and market-readiness of the product.

Join the AI engineering team to develop reliable AI infrastructure for manufacturing systems, focusing on MCP servers, telemetry, and model retraining pipelines.

The Lead AI Engineer will lead the AI Ops team, developing automations and AI agents to improve internal operations and customer service in a fintech setting, while managing engineers and prioritizing tasks effectively.

Develop and optimize AI pipelines for workflow intelligence, experiment with models, and collaborate to integrate AI systems into workflows.

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.

The AI Solutions Architect will architect and deliver AI solutions, integrate AI models into workflows, and define scalable data architectures while collaborating with stakeholders and ensuring system reliability.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.