Top Artificial Intelligence Jobs in Portugal

The Senior AI Compute Infrastructure Engineer will manage and optimize GPU and accelerator clusters for AI workloads, collaborate with teams, and ensure reliable performance and cost efficiency.

Provide research and advisory to global CFOs and Controllers on transforming controllership processes (AP, AR, financial close) using AI, automation and finance technologies; produce published research, vendor evaluations, and client-facing presentations; collaborate with analysts and deliver strategic, actionable recommendations to improve financial reporting and automation outcomes.

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.

Lead engineering enablement across eight companies to cascade CTO AI vision into team discipline. Detect and package successful practices, run cross-company diffusion, operate cadence of validation and demos, measure adoption and outcomes, triage deeper needs to PoCs/workshops, and capture reusable artifacts and metrics.

As a Staff/Senior AI Product Engineer, you will build AI-powered product features, enhance the tech stack, and design AI workflows while collaborating with product teams. Your focus will be on agent-native architecture and improving the codebase for AI agents.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

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

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.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Own and improve Primer's GTM intelligence: maintain dashboards and semantic models, train BI/LLM models (Omni/Claude), surface pipeline/account signals, ensure correct Salesforce modeling, build revenue-driving models and GTM AI workflows, partner with data engineering and RevOps, drive adoption, and promote self-serve data literacy.

Design polished, user-centric mobile and web interfaces for BJAK's AI and financial products. Create wireframes, flows, prototypes and high-fidelity UI, maintain the design system, collaborate with PMs and engineers, iterate using feedback and analytics, and ensure accessibility and responsiveness across devices.

Lead end-to-end product design for complex enterprise products, rapidly prototyping near-functional AI-assisted workflows, collaborating with engineers, presenting to stakeholders, and delivering accessible, compliant designs in a hybrid Lisbon setup.

Join as the first Lisbon-based full stack generalist to build and scale an AI-powered patient recovery platform. Work across AI agent orchestration, prompt engineering, telephony/messaging integrations, dashboards, campaign management, and clinic system integrations to expand the product across markets.

Design and implement execution primitives for AI/agent workflows in Kestra's Java core, build and maintain plugins to connect LLM providers and agent frameworks, convert agent use cases into reusable blueprints with product, and ensure AI executions are observable, debuggable, correct, and reliable.

Own AI workflows product: discover and validate AI use cases with customers, define roadmap and specs, create reusable blueprints with engineering, and prioritize what not to build.

As an AI Solutions Engineer, design and implement AI solutions, collaborate with data teams, and apply advanced engineering techniques to improve AI models, ensuring scalable and robust architectures while translating business needs into AI applications.

Deploy and integrate ICEYEs intelligence platform into secure, often air-gapped environments. Build containerized applications, data pipelines, RAG systems, and AI agents (LangChain/LangGraph). Fuse SAR and multi-source intelligence, prototype mission-focused tools, train analysts, and iterate with customer feedback. Travel ~40-60% and obtain high-level national/NATO security clearances.

Lead prompt engineering initiatives, coach and support business users on AI tools, create best practices and training, evaluate AI platforms, mentor junior staff, and document technical learnings to integrate AI into workflows.

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 end-to-end implementation of QVAC-powered AI solutions, managing client engagement, cross-functional coordination, deployment roadmaps, governance, and production rollouts. Translate business needs into technical deployment strategies, track multiple concurrent projects, and ensure alignment between clients and engineering while documenting architectures and managing risks and escalations.

The Senior SW QA Engineer will collaboratively ensure high quality in optical networking solutions through automated testing, Agile ceremonies, and continuous improvement of QA practices.

Support the Enterprise AI PMO by maintaining the AI initiatives portfolio, coordinating updates across teams, managing programme inbox and governance processes, preparing leadership reports and dashboards, surfacing risks and dependencies, and improving reporting and operational processes using AI-enabled tools to scale the programme consistently.

Lead prompt engineering initiatives and provide technical enablement to business users: develop prompt best practices, coach and train stakeholders, integrate AI tools into workflows, evaluate AI platforms, mentor junior staff, and document technical learnings and case studies.

Enable engineers to generate certified AR5 documentation using internal LLM tools. Act as human-in-the-loop to validate AI output for technical accuracy and aerospace/defence certification compliance. Build templates, authoring standards, version control and traceability, and collaborate with systems, avionics, RF, payload, and quality teams.

Owner of AR5 technical documentation: enable engineers to generate certified docs using internal LLM tools, validate AI-generated content for technical accuracy and certification compliance, build templates and docs-as-code practices, govern versioning and traceability, and collaborate with systems engineering, avionics, RF, payload and quality teams.