Top Artificial Intelligence Jobs in Spain

Lead AI projects by partnering with business leaders to translate challenges into AI solutions, overseeing the entire development process and mentoring teams.

As an AI Product Manager, you'll shape the AI product roadmap, collaborate with cross-functional teams, and ensure AI technologies meet user needs and business objectives.

As an AI/ML Engineer, you will develop and optimize machine learning models for mobile applications, collaborate with teams to enhance user experiences, and implement AI techniques to improve app performance.

As an AI Engineer, you will build AI agents for preventive health, focusing on reasoning, clinical workflows, and ensuring reliable production systems.

As a Senior AI Product Manager, you will own the AI Travel Agent product, leading the full post-booking servicing scope while collaborating with engineering and customer success on product discovery and delivery.

Build production AI-native systems for BJAK's neobank: AI agents, RAG/LLM apps, tool-calling, automations and copilots for onboarding, KYC, support, risk, CRM and operations while addressing accuracy, hallucination, latency, cost, security and compliance.

Join the AI Engineering team to design, build, deploy, and scale production AI systems. Translate business problems into AI solutions, industrialize ML models, design AI pipelines and platforms, ensure performance and monitoring, and drive MLOps best practices across architecture and governance.

Design and lead AI solutions across various technologies; collaborate with teams, support the sales cycle, and provide customer guidance.

As the AI Tech Lead, you'll drive Fever's AI transformation by leading teams to build scalable AI initiatives, enhancing business operations through innovative solutions and stakeholder management.

The role involves owning creative execution for digital marketing campaigns, designing video and static assets, leveraging AI for production, and mentoring junior designers.

This role involves managing Microsoft Commercial Marketplace integrations, evaluating opportunities, conducting feasibility assessments, and leading R&D for novel API integrations and enhancements.

Provide legal counsel on AI and privacy across customer, partner and supplier contracts; lead EU AI Act and ISO 42001 readiness; advise on IP, data protection, incident response, audits and regulatory engagement; produce playbooks, training and negotiation support for commercial teams.

Design, develop, deploy, and maintain scalable AI/ML systems and pipelines. Apply MLOps/LLMOps/AgentOps best practices, run large-scale experiments, build engineering infrastructure for batch and real-time workflows, and integrate models into business applications with monitoring and APIs. Collaborate with scientists, engineers, and product teams to deliver end-to-end solutions using Python, MLflow, Azure, and Databricks.

Remote AI/ML Architect to assess current AI/ML landscape, document requirements, and propose SDLC, governance, and deployment approaches. Provide recommendations to architecture and ICT management. Onboarding in the Netherlands (first week). Candidates must be based in Europe with a valid work permit.

Design and document the current AI/ML landscape, capture requirements, propose SDLC approaches and tooling, and advise architecture and ICT management on AI/ML solution design, governance, and deployment. Remote role with first-week onboarding in the Netherlands.

Design and build LLM-powered tools, agents, and automations to streamline internal processes across teams. Scope, implement, integrate, and ship agents and automations (LLMs, RAG, tool use) with measurable productivity metrics, integrating with systems like Slack, Ashby, and BigQuery.

Lead migration to scalable cloud infrastructure, build and optimize high-concurrency React/Next.js and Node.js applications, deploy and tune production LLM integrations (OpenAI/Groq), and implement monitoring and cost-efficient reliability practices.

Lead and build Axelera's AI Infrastructure Systems division to deliver datacenter-class hardware from accelerator cards and OAM/UBB modules to 1U/2U racks. Own architecture, schematics, PCB/layout review, power/thermal/mechanical design, BMC/firmware, bring-up, validation, qualification, NPI, and ramp with CMs/ODMs. Align roadmaps with silicon, SDK, and product teams, engage customers and partners, set engineering processes, manage budget and vendor relationships, and mitigate technical risks through hands-on leadership.

Lead design, training, and evaluation of LLMs for translation and language-quality tasks; build robust evaluation frameworks; architect agentic multi-model workflows; own model development from data curation to production; run reproducible experiments; collaborate with product and engineering and mentor researchers.

Lead design and delivery of AI-powered features for CLion and C++ workflows. Architect AI integrations and agent tools, prototype and validate debugging, code-understanding, refactoring, and navigation workflows, build benchmarks and evaluation frameworks, and collaborate with product, ML, QA, and engineering teams to set technical direction and roadmap for AI-assisted C++ development.

Own acquisition, onboarding, and activation for JetBrains AI. Improve product entry points, trials, demos, and onboarding flows. Lead experiments, analyze funnels and cohorts, remove friction, and partner with design, engineering, analytics, marketing, and monetization to drive activation and conversion.

Design and implement agentic tools, translating product needs to production, scale prototypes, improve semantic search, build evaluation pipelines.

As a Senior AI/ML Engineer, you will develop and deploy AI initiatives, focusing on ML solutions and ensuring robust software integration. Responsibilities include coding, MLOps implementation, Agile delivery, and collaboration with stakeholders to translate business needs into technical solutions.

As an AI Machine Learning Engineer, you'll develop and deploy AI solutions, implement MLOps workflows, and partner with stakeholders to translate business challenges into technical requirements.

Lead AI engineering initiatives by establishing platform strategies, managing talent, enforcing technical standards, and ensuring the operational excellence of AI products.