Top Artificial Intelligence Jobs in Spain

Lead AI and machine learning architecture, mentor teams, drive innovation, and evaluate tools for AI systems development across global teams.

Lead the design of scalable data and AI solution architectures on Google Cloud Platform, supporting implementation, troubleshooting, and optimization of data initiatives.

Lead the development of computer vision systems for scene understanding, manage technologies, mentor engineers, and stay updated on AI trends.

The AI Engineer will design, build, and deploy AI solutions, focusing on data analytics and machine learning, and collaborate with interdisciplinary teams.

The AI Full Stack Software Engineer will design and develop applications for AI initiatives. Responsibilities include building user interfaces, backend services, and integrating AI applications with other systems while ensuring security and compliance.

Lead implementation of AI governance frameworks and policies, ensure regulatory alignment (e.g., NIST AI RMF, EU AI Act), perform AI risk assessments and mitigation, coordinate with AI/ML engineers on asset management, support reporting and disclosures, and advise cross-functional stakeholders on responsible AI practices.

Remote, asynchronous role evaluating AI-generated Catalan text and audio for accuracy, tone, grammar, and cultural relevance. Provide corrections and constructive feedback via an online platform, ensuring consistency and quality across evaluations. Expect approximately 10 hours of work per week.

Design and implement backend business logic and orchestration for AI coding agents, integrate agents with product surfaces, external APIs and CLIs, build highly concurrent asynchronous workflows, improve context handling and failure recovery, collaborate with product and ML teams, and own technical design and code quality.

Manage SEO and Generative Engine Optimization (GEO) for consumer and e-commerce brands: develop SEO/GEO strategies, perform technical and on-page audits, optimize content and structured data, track AI citation and AI share-of-voice, run link-building and content programs, and collaborate with cross-functional teams to translate insights into client-ready recommendations and proprietary AI marketing playbooks.

Advise customers and internal teams on applying AI within Frontify, design AI-enabled solutions (LLMs, agentic workflows, MCP, RAG, APIs), partner with Sales and Customer Success, influence product roadmap, document repeatable use cases, and create enablement materials to scale AI consulting.

Design, prototype, and ship AI-powered features and agent/LLM workflows for analytics and large datasets. Rapidly iterate with user feedback, integrate agentic components with internal tools, and ensure scalable, production-grade solutions while collaborating across the team.

Design, build, and deploy agentic AI and multi-agent systems for end-to-end supply chain automation. Integrate LLMs, RAG, and vector databases, implement cloud-based production solutions with MLOps, CI/CD, Docker/Kubernetes, and measure operational impact.

Lead a team of four finance business partners supporting CommBank's Data & AI portfolio. Own budgeting, forecasting, reporting, variance analysis, investment cases, financial modelling, governance and commercial advice to senior technology leaders. Drive process improvements using data and AI and influence investment priorities across platforms.

The Senior Manager will design and deliver AI-enabled financial crime detection capabilities using data analytics and machine learning while ensuring compliance with governance and regulatory standards.

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.

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

Design, build, and operate an internal AI Background Agents Platform: implement secure stateful runtimes, sandboxing, CI/CD and GitOps pipelines, progressive delivery, observability (tracing/monitoring), and developer-facing tools to enable teams to build, test, and deploy autonomous LLM-backed agents.

Design, deploy, and maintain production-scale AI/ML systems for personalization, semantic search, and RAG. Own vector database strategy, data models in BigQuery, embedding and retrieval pipelines, and GCP-based AI services. Partner with product and marketing teams and set engineering standards for reliability and production ML.

Lead a new AI Ops Agents team to design, ship, and scale production-grade automations and multi-agent systems. Own delivery and development of three engineers, build RAG pipelines, maintain AI tooling (Claude/Anthropic ecosystem), prioritize cross-team requests, rapid prototype integrations with enterprise platforms, and upskill engineering teams in practical AI usage.

Manage HR data quality and AI readiness by investigating data issues, performing root-cause analysis, defining remediation actions, and implementing validation/automation. Partner with Workday, HR, Payroll, and IT stakeholders to enforce global data standards, monitor anomalies, and support data standardization for reporting and AI/ML use.

Design and build backend services, APIs and workflows for an AI neobank app. Integrate with banks, payment gateways, insurers and data providers. Ensure reliability, security, observability, reconciliation and operational readiness for regulated financial products while partnering with product, mobile and operations teams to deliver scalable customer journeys.

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.

Build end-to-end customer-facing and internal features for an AI neobank app: web flows, backend APIs, admin tools, dashboards, and operational systems. Integrate APIs, manage data flows, improve production reliability, and iterate using analytics and feedback. Collaborate with product, design, mobile, and operations teams and reduce manual work through internal tools.

Build and productionize AI-native workflows, assistants, and automation for a neobank app. Integrate LLMs, RAG, agents, APIs, documents and business systems; design evaluation, monitoring and fallback flows; prototype, test with users, and ship reliable AI systems across customer support, CRM, onboarding, claims, payments and operations.