Top Artificial Intelligence Jobs in Portugal

Serve as the founding customer-facing engineer for Kimchi, leading product demonstrations, customer workspace setup, inference API integrations, model routing optimization, and governance policy implementation. Configure agent workflows, integrations, budgets, cost attribution, and access controls. Translate customer feedback into product improvements while identifying opportunities for revenue expansion. The role combines hands-on LLM and inference expertise with customer enablement and commercial thinking in a remote-first environment.

Owns marketing projects from planning through launch and performance tracking. Develops content, community, social media, and brand strategies; builds messaging playbooks; analyzes audience feedback and campaign metrics; manages cross-functional initiatives; grows digital audience engagement; tests new channels; and handles public-facing situations. The role requires hands-on marketing execution, AI experience, consumer brand knowledge, and strong global communication skills.

Leads one or more engineering teams, providing strategic and technical direction, guiding delivery, workforce planning, hiring, resource allocation, and engineering performance. Coaches and develops engineers, drives continuous improvement and organizational change, supports AI adoption, aligns engineering priorities with business goals, and builds stakeholder relationships. The role also guides technical decisions, tracks team health and business impact, and ensures products deliver customer value.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Serve as a technical-strategic partner for AI Decisioning customers, leading use-case delivery from discovery through go-live and expansion. Collaborate with engineers, executives, marketers, and IT stakeholders to define requirements, explore customer data, recommend marketing improvements, manage project risks, and develop delivery best practices. The role also contributes to AI Decisioning product strategy and requires customer-facing consulting, strong communication, and 10–25% travel.

Own enterprise customers’ AI adoption roadmaps from deployment through expansion. Partner with executives to define AI strategies, coordinate Product, Services, Sales, Success, and partners, and guide solution design and technical escalations. Track adoption, automated resolution, retention, and expansion metrics to drive measurable outcomes. Advise on responsible AI, data governance, compliance, and sustainable implementation while leading success planning, stakeholder alignment, and renewal-focused engagements.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.

Lead customer deployments of Kubernetes and vCluster on bare-metal GPU infrastructure, configuring GPU nodes, networking, storage, RDMA, and InfiniBand. Validate production-ready managed Kubernetes environments, troubleshoot complex infrastructure, transfer operational knowledge, document reusable deployment playbooks, and provide feedback to Engineering and Product. Support pre-sales proof-of-value engagements and help AI cloud and factory customers independently operate and scale their platforms.

Own test planning and management for native iOS, Android, and web applications. Design and maintain Xray test cases and plans, perform manual testing, develop and improve automation, expand test coverage, and support defect investigation and resolution. Collaborate with development teams in an Agile environment while promoting AI tools in QA workflows and contributing to continuous process improvement.

Designs and deploys enterprise AI solutions for finance planning, forecasting, and performance management. Builds multi-agent systems, integrates large language models and Retrieval-Augmented Generation into enterprise workflows, develops AI-powered analytics, and implements monitoring, evaluation, testing, governance, and scalable deployment practices. The role partners with Finance, Data Science, and Technology teams to deliver measurable business impact.

Lead end-to-end AI initiatives across Commercial Intelligence, from prioritization and proof-of-concept through production and adoption. Drive AI transformation, identify and scale use cases, evaluate tools, align technical and non-technical stakeholders, and communicate AI concepts to leadership. Build an AI-first culture through workshops and communities of practice while ensuring rigorous attribution and measurement. Partner with data science and engineering teams to deliver measurable business outcomes.

Leads end-to-end AI initiatives across Commercial Intelligence, from prioritization and proof of concept through production and adoption. Drives AI transformation, evaluates emerging tools, builds an AI-first culture, manages technical and business stakeholders, communicates AI concepts to senior leaders, and ensures rigorous measurement and attribution. Requires strong AI/ML knowledge, hands-on Python and data ecosystem experience, and leadership of complex cross-functional projects.

Manage multi-country payroll operations, compliance, audits, controls, vendor relationships, payroll analysis, and process improvements. Lead payroll system automation and scalability initiatives while ensuring accurate and timely processing across jurisdictions. Partner with finance, HR, treasury, and external providers, monitor regulatory changes, and mentor a global payroll team in a distributed technology environment.

Lead adoption of Sovos’s Core and AI Platform capabilities across engineering teams. Embed with teams to understand codebases, remove adoption blockers, contribute code using AI-assisted development, and create reusable guidance and automation. Establish standards for AI coding assistants, prompt engineering, code quality, and workflow integration. Collaborate on testing and deployments while addressing security and architectural considerations. Mentor engineers, document best practices, and communicate effectively with technical and non-technical stakeholders.

Lead a small engineering team building and shipping AI-powered SaaS features. Set technical direction, establish standards for observability, testing, security, scalable architecture, and AI evaluation, while managing delivery timelines and team development. Remain hands-on by designing and implementing production AI systems using LLMs, embeddings, RAG, vector databases, and related tooling. Partner with Product and leadership on prioritization, architecture, resourcing, and risk management.

Write addictive 1–3 minute AI-generated micro-drama episodes and complete series arcs for women aged 35–55. Create strong hooks, emotional stakes, cinematic scenes, and cliffhangers using Claude, GPT, and other AI tools. Test formats, analyze performance data, identify plot holes and continuity issues, and provide feedback on final episodes. The role is fully remote and requires native-level English, visual storytelling ability, and strong attention to detail.

Join a cross-functional Scrum team to embed quality throughout the software lifecycle. Design and maintain Python and pytest automation aligned with CI/CD, apply AI and LLM techniques for test generation and defect analysis, and perform root-cause troubleshooting. Participate in Agile ceremonies, requirements analysis, and reviews while collaborating with developers, architects, and testers. The role supports recent graduates through mentorship and hands-on experience in automated testing, AI quality frameworks, telecommunications, and optical networking.

Own the global AI roadmap and business automation strategy for the Audio organization. Drive adoption of Claude Enterprise and Salesforce Agentforce, establish AI governance, identify and prioritize automation opportunities, develop business cases, deliver enterprise training, track adoption and value metrics, and partner with IT, product owners, and implementation partners to deliver scalable AI capabilities.

Lead the implementation of Data and AI Governance for clients, translating ambiguous governance challenges into practical operating models. Define ownership and accountability, facilitate stakeholder workshops, embed data quality, metadata, lineage, privacy, security, and responsible AI practices, and support governance forums. Create reusable templates and playbooks while collaborating with Business, Data, AI, Architecture, Privacy, and Security teams across complex enterprise environments.

Design risk-based test strategies and build scalable automated coverage using Playwright, AI coding agents, and CI/CD pipelines. Develop agentic testing workflows, reusable automation frameworks, and AI-powered quality tools. Partner with cross-functional engineering squads to prevent defects, improve observability and release confidence, reduce flakiness, and increase automation coverage. Track quality metrics while enabling developers to integrate reliable automated testing into daily development workflows.

Build modular, config-driven AI video-generation pipelines for mobile gaming advertisements. Integrate generative media models and fal.ai queue workflows, orchestrate asynchronous jobs with retries and resumability, and use FFmpeg for clip assembly, subtitles, overlays, audio mixing, and aspect-ratio formatting. Document configurable workflows so marketing teams can operate them without coding, while optimizing quality, cost, and reliability.

Design, build, deploy, and optimize production LLM agents, MCP servers, RAG and memory architectures, and multi-agent orchestration systems. Develop AI solutions using Amazon Bedrock or Microsoft Foundry, establish evaluation and monitoring frameworks, implement guardrails, analyze failures, and collaborate on scalable AI products. Requires strong experience with agent frameworks, production deployments, cloud AI services, Docker, and CI/CD.

Develop and maintain NLP and generative AI products, including RAG systems, content generation, and recommendation applications. Responsibilities include dataset selection and annotation, rapid prototyping, experimentation, statistical evaluation, production deployment, and iterative system improvement. The role requires staying current with AI advances, communicating technical concepts to stakeholders, and collaborating across international teams while addressing multilingual challenges.

Join Welo Data’s Hungarian contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create and test prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Lead complex AI initiatives, design and scale production-ready intelligent systems, and implement generative AI, LLM, and multi-agent solutions. Provide technical leadership, mentorship, and strategic guidance while aligning AI roadmaps with business objectives. Develop and deploy machine-learning models, predictive systems, optimization solutions, and reliable data pipelines across cloud platforms. Apply model evaluation, feature engineering, interpretability, graph algorithms, time-series forecasting, and probabilistic modeling.