Top Artificial Intelligence Jobs in Madrid

Join Welo Data’s Russian-language AI contributor network for flexible, remote projects involving text, image, and audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. This is not an active opening. Contributors are contacted when suitable projects become available and receive project-specific details about tasks, timelines, and compensation.

Join Welo Data’s Basque contributor network for potential remote AI projects involving data annotation, search and chatbot evaluation, prompt creation, and linguistic or cultural quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation. This is a talent-network opportunity rather than an active job opening.

Join Welo Data’s remote Yoruba AI contributor network based in Nigeria. Projects may involve annotating text, images, or audio; evaluating search results, advertisements, or chatbot responses; creating prompts for large language models; and reviewing cultural and linguistic accuracy. Project duration, scope, timelines, and compensation vary. This is a talent community opportunity rather than an active job opening.

Own new and existing automation machine solutions across Europe. Responsibilities include feasibility studies, solution specification, development project management, lifecycle ownership, documentation, manufacturing supervision, installation, integration, maintenance, troubleshooting, and customer support. The role requires field deployment experience, analytical problem-solving, agile execution, strong communication, and up to 80% travel in Northern Europe.

Lead product direction, roadmaps, standards, and success metrics for major areas of KIRA’s AI neobank app. Guide PMs, product owners, designers, and engineers across multiple squads and financial services, including insurance, payments, savings, investing, and travel. Translate regulatory and business constraints into product decisions, drive launch quality, and foster rapid, user-focused continuous improvement.

Own product areas for KIRA’s AI stockbroking and financial services applications. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial workflows; and use research, feedback, experiments, and performance data to improve products after launch.

Lead engineering execution and technical direction while remaining approximately 75% hands-on. Responsibilities include developing LLM- and AI-powered products, coding, code review, debugging, platform performance, sprint planning, cross-functional coordination, technical mentorship, recruiting, and supporting engineers’ growth. The role partners closely with founders and product teams and offers a path toward Engineering Manager responsibilities.

Own relationships with 40–50 enterprise EMEA clients, leading onboarding, product adoption, usage monitoring, renewals, and account expansion. Help build scalable customer success playbooks, manage NRR and GRR KPIs, and contribute to team OKRs. The role requires demonstrating value for technical SaaS products, navigating complex stakeholder environments, solving customer challenges, and driving commercial outcomes.

Design and improve mobile health coaching experiences focused on behavior change, AI-generated coaching, gamification, and user engagement. Collaborate cross-functionally to develop innovative UI/UX solutions, using user psychology, UX research, data analytics, and rapid experimentation to inform decisions. Generate and present original design hypotheses, validate solutions, and improve customer journeys, motivation, habits, and long-term loyalty.

Own AI Investing product areas across financial services, defining user problems, product scope, metrics, roadmaps, and launches. Partner with engineering, design, data, operations, compliance, and business teams to simplify complex financial journeys. Use research, feedback, experiments, metrics, and production insights to improve decisions and iterate after launch. Balance speed, user experience, business impact, compliance, and operational complexity while driving execution with high ownership.

Leads global commercial customer data governance, Customer 360 strategy, segmentation, data quality, reporting, and insight initiatives. Owns customer definitions and hierarchies across SAP and Salesforce, establishes governance and KPI standards, and aligns reporting and analytics investments with business value. Partners cross-functionally to improve data quality, reporting adoption, forecast accuracy, and AI readiness while driving change management and value realization across the commercial organization.

Build reusable AI developer tools, RAG knowledge systems, and AI-assisted SDLC workflows. Integrate coding assistants and design-to-code tooling, define secure observable patterns, and own reliability, usage, and cost for internal AI platforms.

Lead AI transformation across Sales, Marketing, Customer Success, Partnerships, and Revenue Operations. Identify high-value opportunities, design and deploy production AI agents, agentic workflows, automations, integrations, and enterprise solutions, then drive adoption and measure business impact. Partner with functional leaders, make sound decisions about AI suitability, redesign operating models, improve reliability and governance, and mentor colleagues while establishing reusable standards across the organization.

Lead the strategy, development, deployment, and scaling of AI-powered health products across governments and public health systems in the Global South. Own product roadmaps, execution, stakeholder adoption, partnerships, grant development, and portfolio expansion. Collaborate with engineering, data science, government, donor, and implementation teams to embed sustainable, measurable AI solutions across Africa and Southeast Asia.

Designs and delivers AI-native solutions across business functions including People, Legal, Finance, and Operations. Responsibilities include identifying transformation opportunities, building and deploying AI agents and automated workflows, integrating enterprise systems, driving adoption, measuring business impact, applying governance and human oversight, and mentoring colleagues. The role partners with functional leaders to redesign operating models and continuously improve production AI solutions.

Own product marketing for Cyara’s Agentic AI assurance products, including positioning, messaging, go-to-market launches, competitive intelligence, sales enablement, technical content, and cross-functional collaboration. The role targets enterprise buyers through sales-led motions and requires measurable pipeline impact, strong writing and presentation skills, and comfort working with technical teams. Experience in AI, contact centers, QA, testing, observability, or monitoring is advantageous.

Leads enterprise AI adoption programs from assessment through workshops, hands-on enablement, adoption measurement, and team self-sufficiency. Builds client relationships, develops internal AI champions, creates reusable prompts and templates, ensures compliance with data-governance and responsible-AI policies, reports business impact and ROI, and identifies expansion opportunities. The role requires practical AI fluency, strong facilitation, change-management expertise, customer success capabilities, and executive communication skills.

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.

Leads Workday HRIS solution design, configuration, testing, implementation, reporting, security, and support across Core HCM, Talent, and Recruiting. Builds AI-enabled HR automation, ensures data governance and compliance, mentors analysts, manages releases and projects, and advises HR leaders on technology strategy and process improvements.

Build and operate Kraken’s internal AI platform, including governed integrations, authentication, internal tooling, evaluation systems, spend controls, identity and access controls, provisioning, vendor configuration, and policy enforcement. Provide technical enablement through documentation, deep dives, and office hours while supporting teams and administering the enterprise AI estate.

Design, deploy, and maintain large-scale HPC/AI clusters including monitoring, storage, networking, virtualization, job schedulers, CI/CD, and automation tooling. Troubleshoot from bare metal through OS and application stacks, document standard methodologies, and support R&D and POCs for optimized AI and GPU computing workflows.

Own end-to-end infrastructure delivery for strategic physical AI customers, from discovery and architecture through production rollout. Build cloud compute orchestration, platform services, onboarding environments, observability, security, and cost controls for simulation, training, inference, and batch workloads. Debug across infrastructure layers, productize recurring customer needs, and shape the physical AI platform roadmap. Partner with customers, Field CTO, Product, and Engineering while using AI coding tools to accelerate production engineering.

Design, train, and evaluate large multimodal and vision-language-action models for robotic agents. Develop reinforcement and imitation learning methods, embodied datasets, simulation environments, world models, planning systems, and sim-to-real experiments. Build robust research software and distributed training infrastructure, validate approaches on physical robots, and collaborate with research and engineering teams to deploy reliable systems. Communicate findings through technical reports, open-source releases, demonstrations, and publications.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

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.