Top Artificial Intelligence Jobs in Madrid

Leads Pfizer’s enterprise applied AI strategy, architecture, governance, operating model, and transformation efforts. Drives portfolio-level technical decisions, reusable capabilities, standards, and measurable business outcomes. Provides hands-on architecture and code review using modern AI and agent frameworks while leading engineers, contractors, and vendors. Oversees quality, security, performance, spending, and technical direction, mentors technical leaders, and evaluates emerging technologies and industry trends.

The VP Field Marketing is responsible for leading marketing strategy and execution in Europe, focusing on demand generation, brand awareness, and pipeline development while collaborating cross-functionally and driving a data-driven culture.

Lead global marketing and corporate communications to define Multiverse's narrative, positioning, and GTM for AI/quantum products. Partner with the CEO, build and scale the marketing & communications team, own product messaging, PR, executive positioning, agency relationships, and measure impact on awareness and enterprise pipeline.

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

Owns commercial success, revenue, and strategic relationships for embedded HR technology partners. Responsibilities include managing a $10M+ annual bookings target, developing partner sales motions, enabling partner sellers, driving pipeline and ARR growth, resolving commercial issues, leading executive business reviews, expanding partnerships, coordinating cross-functional teams, and managing partner account managers and embedded sales leads.

Lead a cross-functional squad to define product vision, roadmap and deliver new features for institutional English assessments. Translate business needs into requirements, write and prioritize epics and user stories, run agile ceremonies, collaborate with UX/development/marketing/operations, use data to iterate, and mentor colleagues to achieve measurable business outcomes.

Leads digital transformation across procurement by implementing and optimizing SAP, Coupa, ERP, e-sourcing, and supplier management technologies. Oversees data governance, integration, process improvement, category and spend analytics, supplier performance monitoring, and cross-functional project delivery. Evaluates emerging capabilities such as AI and RPA, manages stakeholder relationships, mentors team members, and drives procurement technology innovation and operational efficiency.

Build Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

Lead and develop Feedzai’s EMEA Solution Consulting team, remove operational blockers, and drive enablement and self-sufficiency. Partner with the EMEA General Manager and regional stakeholders on go-to-market execution, resource allocation, deal strategy, strategic pitches, and executive engagements. Collaborate with Sales, Product, Engineering, and Delivery to align market requirements, influence roadmaps, and ensure effective post-sale handoffs. The role is remote and requires up to 30% travel across EMEA.

Owns planning, activation, optimization, testing, budgeting, and reporting for paid campaigns across TikTok, Meta, and YouTube. Manages $1M+ budgets, presents data-driven recommendations to clients, tracks platform changes, and partners with strategy and creative teams. The role also mentors a Paid Media Executive and establishes team standards for campaign QA, reporting, naming conventions, and optimization practices.

Own the AI agenda across Customer Operations by identifying, implementing, monitoring, and optimizing AI features such as chat and email agents. Manage multiple concurrent projects, align stakeholders, translate operational pain points into automation opportunities, and improve processes across Customer Support and Payments, Fraud & Verification. Track post-launch performance, resolve issues, and drive continuous operational excellence through analytical, creative, and cross-functional problem-solving.

Design and deliver AI-powered experiences for Datadog Notebooks. Build reliable backend services integrating LLMs and AI agents, manage model nondeterminism with evaluation/testing frameworks, partner with product/design, provide technical leadership, and operate production systems (on-call).

Design and develop enterprise Java applications while creating, deploying, and integrating AI, machine learning, LLM, and generative AI solutions. Build APIs and integration services, contribute to software architecture and code reviews, and support public-sector digital transformation initiatives. Ensure solution quality, performance, scalability, and security across production environments.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, including LLM inference infrastructure, RAG, AI agents, and evaluation/observability. Design and run experiments (A/B tests), optimize systems for production performance and reliability, and iterate rapidly with product and design partners.

Lead research and advisory on application security for enterprise applications (ERP/CRM). Produce thought leadership, client-facing insights, presentations, market analysis, and support sales. Mentor analysts, drive research agenda, improve processes, and advise CIOs on security strategy, vendor evaluation, metrics, and vulnerability testing across major vendors (SAP, Salesforce, Workday, Oracle).

Senior individual contributor producing thought leadership and pragmatic insights on enterprise AI and emerging technologies. Advise C-suite, research market trends, create presentations, support sales and peer review, mentor junior analysts, and drive research process improvements while engaging clients and presenting at industry events.

Support Spain (and other markets) by building consistent KPIs and AI-accelerated reports, analysing portfolio and market data to improve NOI and operational performance, driving AI adoption, supporting reporting, testing, systems optimisation, due diligence, and cross-functional data initiatives to inform decisions and process improvements.

Define and enforce enterprise architecture for Migrant Solutions. Design and implement software landscapes, APIs and web-based applications. Create roadmaps, plans, POCs, and technical guidance. Track risks and ensure solutions align with organizational requirements and enterprise architecture.

Own the end-to-end AI-powered content process: develop prompts, generate and edit SEO-friendly articles, fact-check, optimize for search, repurpose content, maintain editorial guidelines, and publish via CMS while improving AI workflows and collaborating with writers and SEO specialists.

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.

The Chief Data & AI Officer will lead the establishment of a company's data and AI infrastructure, ensuring reliable information capture, decision-making processes, AI system integration, and compliance with governance standards.

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.

Design, build, and optimize high-performance AI infrastructure systems to support intelligent agents, ensuring reliability and scalability for millions of users.