Top Artificial Intelligence Jobs in Lisbon

Designs and implements AI, automation, and analytics solutions for supply chain. Develops data models, governance, reporting, and advanced analytics; collaborates with process owners to enable data-driven decisions and trains/supports business users.

Lead deployment and scaling of AI/ML models, agentic tools, and automation across R&D. Drive MLOps, platform integration, compliance, stakeholder partnerships, capability building, end-user support, and metrics tracking to deliver measurable value.

Produce narrative-driven long-form AI-generated videos end-to-end: concept, prompting, generation, editing, compositing, motion graphics, color correction, and maintaining character/style continuity using emerging AI video tools.

Join the Compliance team to own AI and e-commerce legal workflows: GDPR and data protection documentation, AI systems inventory, risk assessments, product/feature reviews, contract and IP issue handling, TOS/privacy updates, and monitoring legal developments. Work with the Ethics & Compliance Officer and review uncensored AI content as needed.

Zyte seeks an AI Product Manager to define strategy, roadmap, and execution for AI-related initiatives, enhancing developer experience with AI agents and workflows.

As a Mid/Senior AI Cinematic Video Editor, you will create narrative-driven video content using AI tools, manage production workflows, and maintain visual coherence in storytelling.

Design and build production-grade GenAI platform components and backend services that integrate LLMs, embeddings, and agent frameworks into secure, scalable financial risk products. Define standards, drive architecture, ensure observability and operational ownership, and collaborate with product, data science, and engineering to deliver AI-powered user experiences.

The Product Manager will drive growth for an AI-powered writing assistant, focusing on product strategy, development, AI innovation, and performance optimization, while leading cross-functional teams.

Seeking an experienced Senior Backend Developer to build Ruby on Rails services for chatbots, research Slack & MS Teams ecosystems, and enhance existing systems.

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

Build and maintain AI-powered internal tools and agentic workflows for operations. Ship rapid iterations (multiple daily releases), integrate third-party APIs, own QA, and translate ops feedback into production deployments.

You will create high-performing video ads, manage the editing process, collaborate with teams to develop concepts, and leverage AI tools for video production.

The role involves creating high-performing video ads, managing the editing and post-production process, collaborating on concepts, utilizing AI tools for video content, and optimizing content for various platforms while adhering to brand guidelines.

The AI Go-to-Market Engineer will drive AI system deployments for revenue generation, automating sales processes, enhancing productivity, and providing actionable insights to improve sales efficiency.

The AI Engineering Intern will design, test, and deploy scalable AI systems, integrate models, and work on inference optimization, collaborating with data scientists on complex problems.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

AI Engineers at QuantCo design, build, and implement applied AI systems, working with data scientists to optimize inference, develop scalable solutions, and integrate AI into enterprise operations.

Lead AI-enabled financial planning and strategic analysis, build data-backed business cases, refine unit economics, deliver executive-level insights, integrate ML into FP&A, and track KPIs to drive profitability and strategic decisions.

Design, implement, and optimize AI-driven solutions across the claims lifecycle (intake, investigation, adjudication). Build ML models for data extraction, fraud detection, reserve setting, subrogation, and adjudication decision engines. Collaborate with underwriting, fraud, legal, and IT to integrate models into operations and improve efficiency, accuracy, and compliance.

Lead budgeting, forecasting, and variance analysis while building AI-driven financial models, scenario planning, KPIs, and dashboards. Automate FP&A processes, deliver insights to senior leaders, and collaborate with cross-functional teams to improve forecast accuracy and strategic decision-making.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Lead integration of AI-driven tools into tax provision, planning, and multi-jurisdictional compliance. Design ML/analytics solutions for sales and payroll tax, enhance regulatory filings, support audits, and collaborate with finance, legal, and technology teams. Monitor tax regulation changes, document AI tax models for transparency and governance, and continuously refine models for scalability, reliability, and compliance.

Design and implement AI/NLP solutions to automate insurance policy administration (issuance, endorsements, renewals). Translate policy language into models and rule engines, integrate with PAS, ensure regulatory compliance, monitor model performance, and support underwriting, operations, and exception handling.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.