Top Artificial Intelligence Jobs in Portugal

Manage an SMB customer portfolio as a trusted technical advisor; identify and close new business; support technical discovery, solution adoption, and cloud consumption; build long-term relationships and maintain accurate CRM and pipeline records.

Support pricing and market analysis by collecting and maintaining pricing data, building product correlation benchmarks, preparing shopping files, monitoring market trends, identifying commercial opportunities, and contributing to AI-driven price collection and market intelligence projects.

Lead AI transformation consulting services, engage with clients, mentor teams, and ensure responsible AI practices while driving business development.

As a Senior Manager, Internal Audit - Tech Ops, you will lead audit engagements in pharmaceutical manufacturing, driving improvements and collaborating with senior stakeholders while ensuring high-quality audits and data-driven practices.

Build and own end-to-end features for Chainguard's AI-enabled CI/CD and supply-chain security products. Design, implement, and iterate on integrations like hardened GitHub Actions, container tooling, and agentic AI features. Drive architectural decisions, collaborate with Product and front-end teams, and ship secure, production-ready developer tools.

Lead account-based and integrated growth programs (ABM, events, content, partnerships, paid) to generate engagement and qualified pipeline for enterprise AI customers, coordinating closely with Sales and cross-functional teams and measuring account influence on opportunities.

Design and build production AI agents that analyze ServiceNow Discovery logs, metrics, failures, and infrastructure telemetry; classify issues, identify root causes, recommend corrective actions, and improve Discovery reliability. Integrate OpenAI and Anthropic APIs using RAG and vector databases, convert runbooks into agentic workflows, and implement testing, guardrails, CI/CD, and human approvals. Troubleshoot enterprise infrastructure and network protocols across large-scale environments.

Design, develop, and maintain production-grade agentic AI solutions for customer interactions across email, chat, and voice. Translate business needs into technical implementations, collaborate with software engineers, data scientists, MLOps teams, and stakeholders, and improve software development processes through AI enablement. Apply ML engineering best practices, LLMOps, and CI/CD while sharing knowledge across teams.

The Backend Engineer will develop and maintain features for Restream web services, design backend APIs, ensure infrastructure resilience, and contribute to a collaborative team environment.

Build full-stack software that turns satellite intelligence into mission-critical decisions. Architect and implement deterministic multi-agent orchestration, geospatial RAG with distributed vector consistency for DDIL environments, optimize high-concurrency spatial indexing and queries, and integrate AI/LLM workflows across cloud and edge. Collaborate cross-functionally, ship production systems, and prepare for forward-deployed, customer-facing engineering roles.

Lead end-to-end AI agent product development for Sales and Marketing: define roadmap, own backlog, drive discovery-to-adoption, lead engineers, partner with UX, and ensure secure, scalable production deployments.

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.

Lead AI-driven IT projects from concept to delivery: plan and govern project execution, manage risks and progress, coordinate cross-functional teams and external vendors, implement automation and intelligent agents, and report to executives while ensuring alignment with business objectives.

Design, build, and deploy production-grade agentic multi-agent AI systems for enterprises. Architect RAG pipelines, multi-LLM integrations, LLMOps, observability, safety and cost governance. Lead client engineering engagements, publish reusable patterns and accelerators, measure agentic system quality, and manage an engineering team.

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 the AI function, define roadmap, and build production generative AI systems (voice, chat, document). Split time between hands-on engineering (~40%) and leading the AI team, establishing RAG/agentic workflows, evaluation, observability, and best practices. Collaborate with product and engineering to deliver reliable, user-focused AI features.

Lead architecture and delivery of a production-grade generative AI media platform. Build reproducible, versioned pipelines (node-based or code-first), train LoRAs, integrate control techniques, add automated QC against product references, enable one-click tools for non-technical teams, and own the technical roadmap with design partners.

Seeking a Senior Full-Stack Engineer to develop AI-driven web and mobile applications, focusing on scalable architectures and API integrations. Collaborate with product teams to translate features into technical solutions.

As an AI/ML Engineer, you will develop and optimize machine learning models for mobile applications, collaborate with teams, and analyze data to enhance user experience.

As an AI Product Manager, you will lead the development of AI-powered features, collaborating with cross-functional teams to align products with user needs and business goals, while overseeing the product lifecycle.

The role involves architecting AI solutions for compliance, ensuring regulatory adherence, automating processes, and enhancing team capabilities through technology and training.

Senior technical lead embedding with customer teams to design, architect, and deliver production-grade AI/ML solutions. Drive model optimization, high-performance training (TPUs), efficient serving (vLLM), MLOps, agentic systems, GDPR-compliant private AI, ROI and cost optimization, pre-sales technical support, mentoring, and external thought leadership.

Lead end-to-end technical projects for a Voice AI CX platform: scope, plan, manage releases, align product to customer requirements, track metrics, ensure quality, and communicate status to clients and engineering.

Build and maintain the marketing automation backbone and AI agent integrations. Implement event tracking, data pipelines, CRM customizations, and cross-channel workflows. Prototype agent infrastructure, connect APIs/webhooks, automate go-to-market tasks, and produce analytics and attribution to support growth and experimentation.

The Principal AI/ML Scientist & Engineer will lead a team, focusing on AI/ML strategy and developing data products for business outcomes.