Top Artificial Intelligence Jobs in Portugal

Design, build, and maintain production AI workflows integrating HR, Finance, Operations, and CRM. Implement orchestration, agents, prompts, retrieval pipelines, and evaluation/monitoring to ensure reliable, auditable decision-making. Iterate on model behaviour using feedback and metrics, partner with Data Engineering on infrastructure, CI/CD, and governance, and own decision quality and outcomes.

Build AI-native product features end-to-end: prototype rapidly, ship iterative releases, engage customers for feedback, and own quality, scope, and outcomes. Work in short cycles using agentic coding and modern stack to move from 0-to-1 in a startup environment focused on human-risk cybersecurity.

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.

As an AI Inference Engineer, you will optimize C++ systems for AI model inference on edge devices, collaborating with researchers to deploy and enhance models while ensuring runtime stability and performance.

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.

Design, build, and scale production-grade AI systems and backend services. Develop high-performance REST APIs in Python and C#/.NET, integrate and optimize LLMs and generative AI, implement multi-agent systems, enforce testing and CI/CD, and ensure security, scalability, and reliability in corporate environments.

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.

The role involves designing and operating AI solutions, such as LLM-enabled workflows and integrated systems, ensuring production standards.

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.

The role involves leading design for AI-native products at Synthesia, focusing on improving interaction patterns and enhancing user experience in AI-driven workflows.

Design, build, and scale LLM and generative-AI solutions including RAG pipelines, vector DB integration, agentic workflows, deployment, monitoring, and applying AI safety and guardrails. Collaborate cross-functionally, document work, and mentor/lead depending on seniority.

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.

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.

As an AI Product Manager at n8n, you'll develop AI-driven product experiences, coordinate with various teams, and innovate through user-centric design, focusing on AI trust and building.

Design and implement AWS-based data platform components, build multi-agent automated ETL/ELT pipelines, enable LLM-augmented capabilities (RAG, semantic search), collaborate with engineers, analysts and data scientists, ensure data quality, security, and production readiness.

Lead short-term AI adoption program: build internal AI champions, create usage policies and training, support teams implementing AI tools, contribute to internal AI tool builds, and ensure responsible, secure deployment across distributed teams.

Design and build production-grade agentic AI systems that analyze ServiceNow Discovery logs, metrics, failures, and infrastructure telemetry at enterprise scale. Develop agents for failure classification, root cause analysis, corrective-action recommendations, observability, and reusable runbook workflows. Integrate OpenAI and Anthropic APIs using RAG and vector databases, while applying guardrails and human approval. Build Python APIs, data pipelines, integrations, automated testing, and CI/CD solutions, leveraging infrastructure engineering and network troubleshooting expertise.

Design and build agentic AI systems that analyze ServiceNow Discovery logs, metrics, failures, and infrastructure health at enterprise scale. Develop agents for failure classification, root-cause analysis, corrective-action recommendations, observability, and reusable troubleshooting workflows. Integrate OpenAI and Anthropic APIs with RAG and vector databases, implement testing and guardrails, and deliver production-grade Python software with REST APIs and CI/CD. Apply infrastructure, networking, and operational data expertise to improve Discovery reliability.

Design and build agentic AI systems that analyze ServiceNow Discovery logs, classify failures, identify root causes, recommend corrective actions, and monitor infrastructure health at enterprise scale. Integrate OpenAI and Anthropic APIs using RAG and vector databases, convert operational runbooks into reusable workflows, and develop production-grade Python services, APIs, data pipelines, integrations, testing, and CI/CD automation. The role also requires infrastructure troubleshooting, network protocol expertise, observability, and ServiceNow Discovery knowledge.

Design and build agentic AI systems that analyze ServiceNow Discovery logs, classify failures, identify root causes, recommend corrective actions, and assess infrastructure health at enterprise scale. Develop RAG- and vector database-enabled integrations with LLM APIs, convert operational runbooks into workflows, and build production-grade Python services, APIs, pipelines, testing, and CI/CD automation. Troubleshoot infrastructure and network issues across Linux, Windows, cloud, and ServiceNow environments.