Top Artificial Intelligence Jobs in Spain

Own product areas across KIRA’s AI neobank, including insurance, payments, savings, investing, and travel. Define customer problems, product direction, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify financial products, ship features, monitor performance, and iterate using data, feedback, research, and production insights.

Own AI Investing product areas across financial services. Define user problems, product scope, success metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial products; use research, feedback, metrics, and production issues to improve decisions; launch features, monitor performance, and drive iteration while balancing speed, user experience, business impact, compliance, and operational complexity.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and related services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, compliance, operations, and business teams; simplify complex financial journeys; launch features; monitor performance; and iterate using data, feedback, research, and production insights.

Leads global privacy and AI legal matters for a SaaS employment platform. Advises Product, Engineering, Security, and business teams on privacy by design, AI governance, data protection, workforce data, incidents, regulatory compliance, vendor reviews, transfers, and contract terms. Builds scalable policies, controls, templates, training, and customer-facing trust materials while monitoring global privacy and AI regulations.

Own AI Investing product areas from user problem discovery through roadmap, launch, measurement, and iteration. Define product scope, success metrics, and launch plans while partnering with engineering, design, data, operations, compliance, and business teams. Simplify complex financial journeys, use research and metrics to guide decisions, and balance speed, customer experience, business impact, compliance, and operational complexity.

Own product areas for KIRA’s AI Stockbroking and broader financial services products. Define user problems, scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial workflows; launch features; monitor performance; and iterate using data, research, feedback, and production insights.

Own AI Investing product areas across financial services, defining user problems, product scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial products. Use research, feedback, metrics, experiments, and production issues to guide decisions, launch features, monitor performance, and drive ongoing improvements while balancing speed, user experience, business impact, compliance, and operational complexity.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and related financial services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; and use data, research, feedback, and production issues to drive iterations and improvements.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and related financial services. Define user problems, product direction, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to deliver simple customer journeys. Use data, feedback, research, experiments, and production issues to guide decisions, monitor performance, and continuously improve products while balancing speed, experience, business impact, compliance, and operational complexity.

Own product areas across financial services including insurance, payments, savings, investing, and travel. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial products; launch and monitor features; and iterate using data, research, feedback, and production insights. The role requires strong product judgment, prioritization, writing, stakeholder management, and independent execution.

Own product areas for AI Stockbroking and other financial services. Define user problems, product scope, success metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial products. Use metrics, research, feedback, and production issues to guide decisions, launch features, monitor performance, and drive continuous iteration while balancing speed, user experience, business impact, compliance, and operational complexity.

Own product areas across KIRA’s AI neobank, including insurance, payments, savings, investing, and travel. Define user problems, product scope, metrics, roadmaps, and launches; collaborate with engineering, design, data, operations, compliance, and business teams; simplify financial journeys; and use data, feedback, experiments, and production insights to improve products after release.

Own product areas within BJAK’s AI Investing and broader financial services portfolio. Define user problems, product scope, success metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams. Simplify complex financial workflows, use research and metrics to guide decisions, launch features, monitor performance, and iterate. The role requires strong ownership, prioritization, communication, product judgment, and the ability to execute with limited guidance.

Own AI Investing product areas across financial services, defining user problems, product scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, compliance, operations, and business teams to simplify financial products, launch features, monitor performance, and iterate using data, feedback, research, and production insights.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and related financial services. Define user problems, product scope, success metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify financial journeys, launch features, monitor performance, and iterate using data, feedback, research, and production insights.

Build and maintain cloud infrastructure and deployment pipelines for WAVE. Implement CI/CD, infrastructure-as-code, disaster recovery, and self-serve platforms to enable rapid, reliable AI solution deployment and scaling while ensuring operational resilience and reuse across projects.

Develop and deploy end-to-end AI solutions for a critical public-sector project. Responsibilities include building generative AI, RAG, agentic, AIOps, and LLMOps solutions; designing scalable architectures with vector databases; integrating AI with ITSM, BMC, CMDB, and observability platforms; and estimating costs, performance, and scalability. The role requires at least five years of experience, software engineering expertise, programming skills, and knowledge of microservices, containers, and messaging systems.

Lead AI strategy and adoption across Corporate Functions at DWS. Build prototypes and production-oriented solutions using LLMs, RAG pipelines, and agentic workflows; coach engineering and business teams; run AI adoption programs and a community of practice; evaluate models and tooling; and advise leadership on governance, roadmaps, responsible AI, and financial-services use cases.

Own AI Finance product areas across insurance, payments, savings, investing, travel, and other financial services. Define user problems, roadmaps, success metrics, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify financial workflows; use research, feedback, metrics, and experiments to improve products; and drive rapid launches and post-launch iteration.

Lead AI strategy and adoption across corporate functions by coaching teams, facilitating communities of practice, identifying use cases, and advising leadership. Build and demonstrate RAG pipelines, LLM applications, agentic workflows, prototypes, and integrations. Evaluate AI tools and platforms, guide responsible adoption in regulated financial services, translate capabilities into business value, and turn experimentation into sustained organizational change.

Develop and deploy AI-powered capabilities across product and business teams. Act as a forward-deployed engineer, embedding with finance, sales, marketing, and product teams to introduce agentic methodologies, support AI adoption, shape the company platform and strategy, and translate learnings into scalable solutions. The role emphasizes production-quality code, business impact, adaptability, collaboration, and effective work in a global distributed environment.

Own AI stockbroking and other financial product areas from user problem discovery through launch and iteration. Define product direction, scope, metrics, roadmaps, and launch plans while partnering with engineering, design, data, operations, compliance, and business teams. Simplify complex financial workflows, use research and performance data to guide decisions, manage trade-offs, and drive continuous improvement after release.

Own AI investing and other financial product areas from user problem definition through launch and iteration. Define scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams. Simplify complex financial workflows, use research and performance data to guide decisions, and balance speed, customer experience, business impact, compliance, and operational complexity.

Build and ship full-stack features for a data intelligence SaaS platform, spanning backend services and frontend interfaces. Use AI coding assistants to accelerate development while applying sound engineering judgment. Participate in architecture discussions, code reviews, testing, incident response, troubleshooting, documentation, and knowledge sharing. Partner with product managers to translate requirements into technical solutions. The role emphasizes SaaS architecture, AWS cloud fundamentals, Docker, Kubernetes, CI/CD, agile delivery, autonomy, and production ownership.

Drive enterprise sales of Microsoft Modern Work, AI, Copilot, and cloud solutions in German-speaking Switzerland. Identify customer needs, build relationships with business decision-makers, lead value-based solution selling, coordinate internal specialists and partners, and manage opportunities through forecasting, competitive planning, cross-selling, and closing. The role requires strong German communication skills, technology-related sales or account management experience, and the ability to sell solutions to enterprise customers.