Top Artificial Intelligence Jobs in Lisbon

Build and maintain operating and cash-flow models, apply AI/ML and data techniques to automate forecasts, run sensitivity and scenario analysis, translate strategy into financial outcomes, support fundraising/M&A/pricing, and create dashboards and reports for stakeholders.

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.

Build and scale Jimdo Companion: design agent orchestration, LLM-powered workflows, recommendation engines, APIs and full-stack features; enable AI platform capabilities, collaborate cross-functionally, and drive product-quality AI in production.

Build and ship agent orchestration workflows, integrations, and shared infrastructure for AI-driven growth across paid media, lifecycle, organic content, CRO, incentives, and referrals. Implement monitoring, audit logging, creative generation pipelines, and reliable integrations so domain experts can tune and operate workflows independently.

Build and ship native Android features in Kotlin, improve performance and reliability, integrate backend APIs, collaborate with product/design, and implement AI-assisted on-device experiences where valuable.

Build and ship native Android features for an AI-enabled neobank using Kotlin. Design clean user flows for financial services, integrate backend APIs, improve performance and stability, use analytics to iterate, and implement on-device AI where it improves UX.

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.

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 role involves delivering features across the CRM platform for distributors, using AI tools, handling fullstack development tasks, and collaborating closely with teams and customers.

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.

Design, build, orchestrate, and deploy production-ready AI agents and LLM-based solutions. Partner with domain experts to identify high-value use cases, redesign workflows using AI-first principles, integrate AI workflows into business infrastructure, and support internal AI enablement and training.

Lead Data, Analytics, AI, and GenAI presales activities for strategic enterprise opportunities. Facilitate discovery workshops, translate business needs into scalable architectures, lead RFP and RFI responses, and present solutions to executives. Design end-to-end AI and cloud architectures across Azure, GCP, Databricks, and open-source ecosystems. Advise on AI transformation use cases, roadmaps, governance, and implementation, while mentoring delivery teams and developing reusable frameworks, offerings, thought leadership, and customer success materials.

Design, build and deploy AI-powered solutions (custom copilots, conversational agents, embedded AI) using Microsoft Copilot Studio, Power Automate and Azure AI Foundry. Integrate with Snowflake and enterprise systems, collaborate with stakeholders to define use cases, operationalise models, maintain reliability and governance, and evaluate emerging AI tools.

Develop and deploy production-ready generative AI applications using Python, LLMs, RAG, AWS Bedrock, and OpenAI APIs. Responsibilities include model customization, API integration, data preparation, performance tuning, production deployment, documentation, and cross-functional collaboration. The role focuses on applied engineering rather than research and requires experience integrating AI solutions into business applications.

Lead the development of computer vision systems for scene understanding, manage technologies, mentor engineers, and stay updated on AI trends.

As part of the Advanced Analytics and AI team, you will develop and deploy machine learning models, engage with business functions to create AI opportunities, and support AI capability roadmaps, all while working in a collaborative international environment.

Lead design and build of an end-to-end AI contract-review agent: prompt orchestration, RAG pipelines, fine-tuning, web UI and tooling, data/model infra, deployment (CI/CD/cloud), and product-driven features like assumption mapping and contract diagnostics.

Lead architecture and build an automation and AI-native toolchain (fusing traditional automation with agentic workflows), mentor teams, drive cross-department adoption, standardize practices, and evolve IT operations toward infrastructure-as-code and platform-first models.

Build and improve Restream’s web interfaces and user-facing features for the AI Clips team. Design UI and business logic, collaborate with product designers, participate in code reviews, improve system reliability, and evaluate emerging technologies. The role requires strong JavaScript and TypeScript expertise, advanced React knowledge, CSS preprocessor experience, and familiarity with backend development, cloud infrastructure, containers, and continuous deployment.

Provide customer support through social media and email, represent brands, resolve customer requests, and ensure engaging experiences.

Create high-volume, high-quality marketing content using generative AI and AI agents. Produce video, image, and social content, develop attention-driving campaigns, track AI and culture trends, and iterate quickly with the marketing and founding team.

Build features, prototypes, and demos using modern AI coding tools and agents; iterate prototypes into reliable, scalable production; direct and evaluate AI coding agents; collaborate closely with founders and senior engineers; explore and improve AI development workflows to accelerate product delivery.

Lead AI-native engineering: build and ship production-grade features, convert AI-assisted prototypes into reliable systems, own architecture/security/quality, direct AI coding agents, define engineering standards, and work closely with founders on product and technical strategy.