Top Artificial Intelligence Jobs in Seville

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.

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.

Lead end-to-end delivery of iGaming features, coordinating Product, Development, QA, and Marketing. Manage timelines, resources, risks, third-party integrations, stakeholder communication, and continuous improvement through post-mortems to ensure timely, high-quality releases.

The role involves designing and deploying AI systems for clinical operations, developing models for decision-making, and ensuring AI implementation aligns with data governance standards. Responsibilities include collaborating across teams, enhancing operational efficiency, and advancing AI applications in a regulated environment.

Conduct discovery and audit sessions to analyze support workflows, ticketing systems, and KPIs. Identify automation opportunities and design scalable AI-driven solutions (chatbots, NLP classification, auto-triage, agent assist). Assess client platforms (Zendesk, Freshdesk, Intercom), produce AI readiness assessments and roadmaps, and deliver clear, data-driven recommendations for implementation and ROI prioritization.

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.

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.

Lead strategy, production, and commercial performance for owned casino games. Own roadmap, vendor management, end-to-end production, RTP/volatility strategy, live operations, and post-launch performance.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The Senior AI Compute Infrastructure Engineer will manage and optimize GPU and accelerator clusters for AI workloads, collaborate with teams, and ensure reliable performance and cost efficiency.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

The AI Motion Designer will create marketing videos using AI tools, producing and adapting content for various platforms, and managing the video production process from concept to delivery.

The VP of Business Development will drive commercial growth in Europe, focusing on strategic opportunities with renewable energy stakeholders and building relationships to enhance market presence.

Design and implement execution primitives for AI/agent workflows in Kestra's Java core, build and maintain plugins to connect LLM providers and agent frameworks, convert agent use cases into reusable blueprints with product, and ensure AI executions are observable, debuggable, correct, and reliable.

Own AI workflows product: discover and validate AI use cases with customers, define roadmap and specs, create reusable blueprints with engineering, and prioritize what not to build.

Build end-to-end AI features and prototypes across backend and frontend, prototype AI agent use cases, create UI/blueprints/examples to make AI workflows usable, and ship features quickly in collaboration with product and backend teams.

Lead and own Agent0: co-own roadmap with Product, hire and grow a senior AI engineering team, drive delivery of production-grade agentic AI, set evaluation and monitoring standards, prototype innovations, and provide thought leadership on AI production excellence.

Evaluate and rank personalized LLM responses using multi-turn prompts based on your personal data sources. Design prompts, assess grounding, integration, and helpfulness, perform side-by-side comparisons, write clear rationales with turn references, extract and verify debug info, and maintain strict data hygiene. Provide constructive feedback and detailed annotations while working independently as part of a global evaluation team.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

As a Chatdesk Expert, you'll provide customer support through social media and email, ensuring great experiences, flexible schedules, and work from anywhere.

Senior individual contributor who architects, prototypes, and ships production-grade AI solutions for Finance. Focus areas include agentic AI, multi-agent orchestration, ML forecasting and anomaly detection, RAG and vector-store solutions, responsible AI and governance, and embedding AI into FP&A processes. Partners with engineering, IT, security, and finance teams to productionize systems and establish standards, monitoring, and controls.

Post-sales, customer-facing role that drives developer adoption of AI tooling by designing and running hackathons, Customer Developer Days, and repeatable facilitation infrastructure. Partner with deployment and success teams to diagnose adoption stalls, run high-touch interventions, capture outcomes, and evangelize results. Must be technically credible with developers and able to troubleshoot and demonstrate AI coding tools in real time.

Design, build, and maintain scalable, secure cloud infrastructure across AWS and Azure using Terraform, Docker, and CI/CD. Manage production environments, monitoring, security, IAM, secrets management, automation, cost optimization, and collaborate with dev/DevOps teams to ensure high availability and reliability.

Design, build, and scale ETL/ELT and real-time data pipelines for AI workloads (RAG, fine-tuning, batch inference). Transform unstructured data into vectorized formats, manage feature stores and vector databases, enforce data quality/governance, integrate event systems (Kafka), and collaborate with ML and engineering teams.

Lead end-to-end development and integration of AI features (LLMs/ML) into web/mobile apps and APIs. Design AI-first UX, craft and optimize system prompts, build agentic workflows (LangChain/CrewAI/AutoGen), implement error-handling and hybrid cloud/on-prem deployments, and collaborate within product squads using Agile/Scrum.