Top Artificial Intelligence Jobs in Lisbon

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.

Own the technical infrastructure for an AI-assisted content and design operation. Responsibilities include selecting tools, building automation pipelines, orchestrating agents, designing multistep content workflows, integrating UIs with databases and external tools, maintaining modular systems, reducing manual work, and shaping architecture and roadmap decisions with leadership. The role requires production coding, API integrations, database and vector-search design, RAG implementation, workflow automation, and strong content judgment.

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.

Review and evaluate Arabic-language AI content while supporting customers of a major social media platform through email, chat, and phone. The role requires strong knowledge of generative AI, LLMs, and AI annotation or evaluation platforms, plus fluent Arabic, good English, communication skills, computer proficiency, empathy, flexibility, and availability for night shifts. EU citizenship or a valid Portuguese residence card is required. Previous client experience is beneficial but not mandatory.

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.

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.

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.

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.

Provide customer support for users of major AI advertising platforms in Lisbon. Responsibilities include assisting customers, troubleshooting issues, resolving problems, and creating positive user experiences. The role requires advanced English, technical aptitude, willingness to learn, and a positive attitude. Previous experience is not required, and comprehensive training is provided.

Own AI and automation product initiatives for internal workflows and connectivity platforms. Lead discovery, define roadmaps and requirements, prioritize opportunities, and partner with AI, platform, security, and compliance engineers through delivery. Prototype solutions, establish evaluation and release criteria, manage sensitive-data and human-review requirements, and measure adoption, efficiency, and business impact. The role may later extend AI capabilities into customer-facing products.

Designs, develops, and maintains cloud automations, RPA workflows, AI-powered solutions, and enterprise system integrations. Builds solutions with Microsoft Power Platform, Copilot Studio, Azure AI, SAP, Microsoft 365, SharePoint, and Dataverse. Develops REST APIs and custom connectors, troubleshoots existing solutions, participates in technical architecture, translates business requirements into scalable applications, and supports deployment, monitoring, and continuous improvement.

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 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.

Build and operate production multi-agent AI systems for customer service. Own agent prompts, orchestration, tools, evaluations, deployment, monitoring, authentication, guardrails, and transaction handling. Develop measurable quality frameworks, optimize model cost and latency, and integrate agents with booking, Salesforce, Genesys, and communication channels. Collaborate with engineering, data science, MLOps, product, and customer service teams while enabling broader adoption of agentic AI.

Build and ship production AI systems, including LLM agents, retrieval pipelines, event intelligence, tool integrations, and inference services. Contribute code, tests, observability, evaluation, and monitoring for high-volume real-time systems. Collaborate with platform, product, and applied-research teams while learning to optimize latency, throughput, cost, reliability, and model quality through mentorship and code reviews.

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.

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.

Leads enterprise solution architecture across discovery, consulting, proposals, and delivery. Defines technology vision, designs scalable cloud-native and distributed systems, advises executive stakeholders, governs implementation, and evaluates emerging technologies. Builds reusable consulting frameworks, mentors architects and engineers, leads complex client engagements, and supports pre-sales and upsales. Requires extensive software engineering and architecture leadership experience, cloud expertise across multiple platforms, strong communication skills, and knowledge of Agile, DevOps, CI/CD, and Infrastructure as Code.

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.

Build and maintain PHP and Laravel backend services and APIs for a major product release. Own features from design through deployment and monitoring, integrate agentic AI workflows and LLM-based tooling, optimize performance and reliability, improve security, and mentor engineers. Collaborate independently with a cross-functional team on ambiguous technical challenges while delivering production-ready software.

Build and own production agentic AI runtime components, including context construction, retrieval and tool orchestration, ranking, scoring, guardrails, multilingual quality, latency and cost optimization, and evaluation systems. Diagnose production failures through traces and improve agent reliability for customer-facing commerce applications.

Design, prototype, deploy, and optimize AI-powered features for construction management applications. Apply LLMs, prompt engineering, model selection, fine-tuning, evaluation, embeddings, vector databases, and RAG. Collaborate with product engineers and SREs to build reliable, scalable, observable, secure production systems. Translate user needs into pragmatic AI solutions while contributing production-grade software and staying current with generative AI developments.

Design, deploy, and optimize machine learning and AI solutions, including fine-tuning open-source and commercial LLMs, implementing RAG, and developing generative AI models. Conduct exploratory data analysis and feature engineering, apply traditional machine learning methods, validate solution quality, collaborate with engineers and stakeholders, and maintain technical documentation for reproducibility and knowledge sharing.