Top Artificial Intelligence Jobs in Portugal

Administer and maintain Windows and Linux servers, cloud infrastructure (Azure/AWS), and Microsoft 365. Implement monitoring, automation, performance optimization, AI platforms, and intelligent services. Ensure secure, scalable, highly available systems with strong scripting (PowerShell/Bash), IAM, observability, and cybersecurity best practices. Provide hybrid on-site support in Lisbon.

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.

Fine-tune and post-train open-weight LLMs using methods such as SFT, LoRA, QLoRA, DPO, and GRPO. Build training data and evaluations, diagnose model failures, improve personalization and multilingual behavior, accelerate reproducible training workflows, and deploy models to production. The role involves using real user behavior to guide iterations across a large-scale AI companionship platform, with collaboration across AI, product, web, DevOps, and leadership teams.

Develop and maintain a multi-cloud GenAI platform: design, implement, test, deploy scalable APIs and backend services, build monitoring and KPIs, automate workflows, ensure security/compliance, and collaborate with international teams to continuously improve platform capabilities.

Lead design and build Generative AI applications using LLMs and Azure AI services. Implement, deploy (Azure ML, CI/CD), integrate semantic search and embeddings, handle data engineering, and present solutions to stakeholders.

Lead technical delivery of an AI-assisted operations platform from discovery through implementation and evaluation. Establish technical baselines, validate integrations, design maintainable rules and AI workflows, guide engineers, review code, implement testing and observability, and ensure traceable human-approved decisions. The role requires hands-on architecture, API integration, evaluation, CI, production readiness, and clear communication with business and engineering stakeholders. Travel to an in-person working session in Milan is included.

Lead the architecture and implementation of AI-native product engineering systems, including agent-ready code standards, context infrastructure, self-healing incident workflows, multi-step agentic features, and AI code-review optimization. Ship end-to-end product features, set technical direction, evaluate LLM reliability and trade-offs, and accelerate validated learning through close collaboration with engineering, product, and design teams.

Lead the architecture and implementation of AI-native product engineering systems, including agent-ready code standards, context infrastructure, self-healing incident workflows, multi-step agentic features, and AI code-review optimization. Ship production software, establish technical direction, and partner with product and design teams to accelerate validated learning. The role requires strong backend and distributed-systems expertise, hands-on LLM product experience, and practical use of AI coding tools.

Build data, analytics, machine learning, and internal tooling solutions for a UAV platform team. Analyze flight logs, telemetry, video, and mission data; develop and evaluate ML models; create dashboards, scripts, APIs, and integrations; and support ground and flight testing. The role bridges platform engineering with Data & AI teams, using AI-assisted development to rapidly prototype and productionize solutions. It requires strong Python, SQL, data science, software integration, communication, and aviation or robotics interest.

Produce coordinated, fabrication-ready MEP BIM models for commercial buildings at LOD 350–400 using Revit and ISO 19650 workflows. Maintain families and templates, perform clash detection, and develop Dynamo, pyRevit, and Python automation. Evaluate AI-for-AEC tools using real project data, measure productivity gains, and translate modelling workflows into product requirements, datasets, and acceptance criteria for an AI BIM platform.

Develop and maintain web applications with React and Next.js, support Node.js APIs and backend services, implement new features, and collaborate with product and design teams. The role also involves integrating AI tools, building automations, and creating AI-assisted solutions. Candidates should have 1–2 years of fullstack or software development experience, hands-on AI project experience, and familiarity with AI agents or agentic workflows.

Own end-to-end product design for MEDvidi’s AI Track, creating human-AI interaction patterns for clinical tools. Gather requirements independently, conduct user analysis and validation, prototype directly in code using Claude Code or Cursor, collaborate with product and engineering, accept delivered designs, analyze outcomes, and contribute reusable Storybook design-system components, tokens, and documentation.

Join Welo Data’s Swahili contributor network for potential remote AI projects involving text, image, or audio annotation; search, advertising, or chatbot evaluation; prompt creation; and cultural and linguistic accuracy review. Applicants must be native or near-native Swahili speakers based in Kenya, Tanzania, or the Democratic Republic of Congo, with English proficiency, digital-tool comfort, and strong attention to detail. Projects vary in duration and compensation, with details provided before participation.

Create and evolve Noxus’s visual identity across brand, motion, video, product storytelling, and marketing collateral. Translate complex AI and enterprise technology into clear visual assets, including diagrams, reports, presentations, case studies, and demos. Build reusable design and motion systems, own the video pipeline, and collaborate with founders, marketing, sales, product, engineering, agencies, and external partners in an in-office startup environment.

Develop AI-driven products through hands-on software development and product engineering. Build minimum viable products, solve problems creatively, and help shape future AI applications. The role is available remotely or in Boston and Chicago, with contract options ranging from two weeks to three months or full-time, plus potential revenue sharing.

Manage a portfolio of SMB customers as a trusted technical advisor, supporting solution discovery, cloud adoption, consumption, retention, and growth. Identify and develop new business opportunities through the full sales cycle, maintain customer relationships, and keep CRM records and sales pipelines accurate. The role requires fluent Dutch, strong communication, customer-oriented problem-solving skills, computer proficiency, and eligibility to work in the EU or Portugal.

Leads QA automation strategy across web, API, and backend services. Designs and maintains automated test frameworks, integrates testing into CI/CD pipelines, investigates defects, maintains test environments, and promotes quality practices. Mentors junior engineers and collaborates with product and engineering teams on acceptance criteria and release quality. Applies AI-assisted tools for test generation, debugging, defect analysis, and automation optimization.

Own the vision, roadmap, business case, pricing, P&L, and go-to-market strategy for new software-defined rail products. Identify market opportunities, translate customer needs into requirements, and guide solutions from concept to first paying customers. Coordinate engineering, safety, certification, commercial, and business development teams while balancing certification milestones and customer commitments in a regulated, safety-critical environment.

Own the Vault product roadmap and lifecycle for a sports media asset platform. Lead discovery with customers, define solutions for content ingest, storage, integrations, AI enrichment, metadata, search, rights, and asset monetization. Partner closely with engineering, sales, and customer success, attend customer events, and prioritize product bets that help sports organizations maximize the value of extensive media archives.

Design, build, and ship full-stack production software integrated with agentic AI systems and LLM APIs. Use AI-assisted development throughout the software lifecycle, evaluate AI-generated outputs, track productivity and quality KPIs, and own delivery from design through production support. Collaborate with client engineering teams in Agile environments while contributing reusable components, AI tooling standards, and integrations across application, API, and enterprise AI pipeline layers.

Leads research and thought leadership on AI-driven HR strategy, transformation, governance, workflow redesign, regulatory environments, and value realization. Produces actionable insights across written, visual, video, and presentation formats; advises CHROs and senior HR leaders; analyzes market trends, vendors, technologies, and client challenges; supports sales and conferences; mentors analysts; and improves research processes.

Own daily operations and quality assurance for an internal AI-powered growth platform. Test releases, rule changes, edge cases, and regressions; document and verify bug fixes; monitor platform and agent activity; manage approval queues; evaluate agent output; escalate risks; and maintain test plans, QA checklists, runbooks, and release notes.

Own the end-to-end B2B lead lifecycle, including segmentation, scoring, qualification, routing, automation, AI workflows, and sales handoffs. Develop pipeline health KPIs, analyze conversion and revenue metrics, improve lead-management tooling, and establish SLAs and feedback loops across Marketing, Telesales, Key Account Management, and Global Account Management. The role combines B2B sales strategy, revenue operations, process implementation, stakeholder management, and cross-functional influence.

Assist users of AI advertising platforms by answering questions, troubleshooting problems, and creating positive customer experiences. The role requires advanced English, technical aptitude, motivation to learn, and a friendly attitude. Comprehensive training and opportunities for growth are provided in a multicultural Lisbon-based environment.

Optimize LLM inference on modern GPUs by analyzing GPU architecture, memory access, kernels, and performance bottlenecks. Develop, debug, reverse-engineer, and benchmark CUDA kernels and low-level operations for improved latency, throughput, and utilization. Work with inference frameworks including vLLM, SGLang, TensorRT-LLM, Triton, and FlashAttention. Investigate advanced topics such as distributed inference, quantization, KV cache optimization, and custom GPU kernels.