Top Artificial Intelligence Jobs in Barcelona

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.

Design, build, and ship AI-powered product features from prototype through production. Own architecture, model selection, integrations, evaluation, reliability, cost, and latency. Work across frontend, backend, and infrastructure while establishing reusable AI development practices. Collaborate with engineering and product teams to define requirements, identify risks, and deliver maintainable, monitored, production-ready systems using LLMs, embeddings, RAG, vector databases, and multiple providers.

Build and maintain full-stack internal tools, automated workflows, and customer-facing features using TypeScript, Node.js, and React. Integrate LLMs, AI services, third-party APIs, and external platforms. Use AI coding assistants to prototype, develop, test, and improve reliable software. Collaborate with internal users, product managers, designers, engineers, and the Chief AI Officer in an Agile environment while contributing to architecture, code reviews, UX, security, performance, and continuous improvement.

Lead the company’s Physical AI research and engineering function as a hands-on technical leader. Define research priorities, design and train Transformer-based models, establish rigorous offline and real-world evaluations, integrate systems with physical robots, and analyze failures across data, models, hardware, and environments. Build a focused team, guide technical architecture and experiments, translate customer needs into requirements, and deliver measurable improvements through deployed models, benchmarks, evaluation systems, or data products.

Create narrative-driven long-form videos featuring AI characters, managing the full AI-first production workflow from scripting, prompting, and generation through editing, compositing, motion graphics, color correction, and delivery. Maintain character and scene consistency, experiment with emerging AI tools, refine scalable workflows, and execute independently under creative direction. Content may include stylized and explicit NSFW visuals.

Create narrative-driven, long-form cinematic videos using AI-first workflows, from scripting and prompting through generation, editing, compositing, motion graphics, color correction, and final delivery. Maintain character and scene consistency across sequences, experiment with emerging AI video models, refine production workflows, and independently execute creative direction. The role includes stylized and explicit adult content and requires strong storytelling, technical judgment, rapid iteration, and collaboration.

Lead the development of AI-powered personalized learning solutions, including deep learning, NLP, information retrieval, LLM, and multimodal systems. Define scientific roadmaps, advise senior leadership, collaborate with product and engineering teams, mentor scientists and engineers, and establish machine learning architecture and deployment best practices from research through production.

Build production-grade agentic AI systems that analyze infrastructure discovery logs, classify and correlate failures, troubleshoot root causes, recommend corrective actions, and safely generate probe or pattern corrections. Develop telemetry pipelines and API integrations using Python, Gen AI APIs, RAG, and vector databases. Apply modern SDLC, CI/CD, automated testing, security scanning, and deployment practices.

Build and maintain Quality dashboards in MicroStrategy, translating stakeholder needs into KPIs and reliable visualizations. Develop an AI agent that delivers tailored sales quality guidelines using structured knowledge, prompt engineering, and iterative testing. Collaborate with Quality experts, Data Analysts, and business stakeholders to validate outputs, improve processes through data insights, and present findings. The internship requires SQL, dashboarding, Excel, Adobe knowledge, strong analytical and communication skills, and interest in AI and digital innovation.

Lead an internal product portfolio focused on AI tooling for software development and design systems. Own strategy, roadmaps, product specifications, evaluation standards, adoption, governance, measurement, and sunset decisions. Lead cross-functional teams without direct authority, coach product managers, establish lightweight operating practices, and partner with Legal, Privacy, Security, and IT. Drive AI literacy, enablement, change management, and metric-led reporting while balancing speed, reliability, cost, and data risk.

Translate manufacturing business needs into technology solutions, create AI-assisted development prompts and playbooks, modernize legacy applications, and support secure software delivery. The role involves DevOps, CI/CD, automated testing, cloud-native modernization, responsible AI governance, stakeholder collaboration, and coaching colleagues on AI adoption across global manufacturing IT environments.

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.

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.

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.

Identifies, designs, deploys, and sustains AI solutions within a Wind Engineering subsystem. Partners with engineering leaders to prioritize use cases, integrates AI into engineering workflows, ensures governance and cybersecurity compliance, drives adoption, and monitors solution performance and value. The role develops applications, agentic workflows, copilots, automation, predictive models, and knowledge systems while contributing reusable patterns and innovations to the broader AI community.

Leads the identification, design, deployment, integration, governance, adoption, and continuous improvement of AI solutions across a Wind Engineering subsystem. Partners with engineering and business leaders to prioritize AI use cases, build roadmaps, configure AI applications and agentic workflows, integrate solutions into engineering processes, validate outputs, ensure security and responsible AI compliance, educate teams, and monitor solution performance and business value.

Lead the end-to-end roadmap for internal AI automation, designing and deploying production-grade agents and multi-step workflows. Integrate agents with core business systems, audit processes, quantify automation impact, redesign workflows with stakeholders, define ROI and performance KPIs, and drive adoption through documentation, training, and change management. The role also evaluates AI tooling, reports progress to leadership, and promotes responsible AI deployment.

Build cloud security training labs and technical content using YAML, Markdown, Bash, and Python. Support training-platform troubleshooting, deliver technical demos and workshops, write courseware, and apply instructional design principles. Use AI coding agents to accelerate lab and script development while validating outputs. Collaborate with senior instructors and cross-functional teams while developing technical depth, teaching ability, and presentation confidence.

Own the AI cost visibility product end to end, developing Go backend services, APIs, data processing, and TypeScript/React interfaces. Translate AI spending data into clear FinOps experiences, work closely with customers and product needs, and use AI throughout the engineering workflow. Lead feature design, implementation, release, monitoring, and iteration while setting engineering standards, mentoring peers, and building scalable cloud-based SaaS capabilities.

Own the AI cost visibility product end-to-end, building Go backend services, APIs, and TypeScript/React interfaces. Translate cloud AI spend and usage data into clear FinOps experiences, while driving architecture, reliability, monitoring, and iteration. Collaborate closely with customers and product stakeholders, use AI throughout the engineering workflow, mentor peers, and shape product direction in an ambiguous market.

Own AI cost visibility features end-to-end, from customer problem discovery and system design through implementation, release, monitoring, and iteration. Build scalable Go backend services, APIs, and TypeScript/React interfaces that process and present cloud AI spend data. Apply AI throughout the engineering workflow, contribute to product direction, understand FinOps and AI economics, mentor peers, and uphold reliable engineering practices.

Build and deploy production-grade role-based AI agents for renewable energy asset monitoring, analytics, optimization, and decision support. Design multi-agent architectures, integrate diverse data sources and enterprise systems, create evaluation and testing frameworks, implement observability and traceability, and operate AI services in production. Collaborate with renewable energy experts to ensure outputs are accurate, evidence-based, safe, and operationally useful.

Transforms SAP and enterprise data into executive-ready insights on profitability, margins, costs, KPIs, and value creation. Builds analytical models, dashboards, reporting logic, visualization layers, and data refresh processes. Applies AI-enabled tools to improve analytics scalability and collaborates with Finance and business teams to convert findings into measurable performance improvements.

Define and maintain enterprise AI reference architectures, reusable solution patterns, and MLOps/LLMOps standards. Guide subsystem designs for scalability and reuse, update engineering standard work and QMS for AI, partner with Digital/IT on platforms and integrations, mentor Embedded AI Architects, and serve as technical escalation for high-risk AI initiatives across Wind Engineering.