Top Artificial Intelligence Jobs in Seville

As a Lead Full Stack Engineer, you will drive the technical strategy and development of our SaaS insurance platform while mentoring engineers and overseeing AI integration.

Design and maintain a governed, canonical customer dataset by unifying GTM sources, building enrichment and entity-resolution pipelines, preparing structured and unstructured data for LLM/embedding workflows, implementing monitoring and lineage, and defining standards for AI-ready data across RevTech.

Lead design, training, and evaluation of LLMs for translation and language-quality tasks; build robust evaluation frameworks; architect agentic multi-model workflows; own model development from data curation to production; run reproducible experiments; collaborate with product and engineering and mentor researchers.

Lead research and analysis of the enterprise AI services market, build market-sizing and forecasting models, publish thought leadership, advise C-level clients, present at events, support sales and peer review, mentor junior analysts, and drive research process improvements to deliver actionable insights on AI services and competitive dynamics.

The Senior SEO & AI Search Strategist will lead enterprise customers in SEO and AI search, developing strategies and plans, while advising senior decision-makers and driving measurable outcomes.

The Senior Product Manager will lead the strategic roadmap, conduct market research, manage monetization strategies, and mentor a team while collaborating across various departments.

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

Develop and maintain automation testing frameworks, execute tests, and implement AI-driven quality practices while collaborating with product teams.

Identify and validate high-value AI use cases for financial services, lead discovery workshops, build ROI-driven business cases, map and redesign workflows, define technical requirements and acceptance criteria, prototype solutions with no-code tools, implement AI governance and ontologies, and ensure business-aligned delivery and compliance.

Lead Full Stack Engineer owns design-to-production of an AI-first repossession and remarketing platform. Shape architecture, build scalable resilient services, integrate LLMs/GenAI for validation and document processing, drive technical decisions, reduce technical debt, operate production systems, and mentor engineers while working in cross-functional agile teams.

Support Shopify administration and Flow automations, maintain Google Apps Scripts and API integrations, manage access and SaaS subscriptions, configure Recharge subscription flows, and document processes. Use AI tools (Claude, ChatGPT) and n8n to build automations, test end-to-end, and liaise with vendors and internal teams to keep e-commerce systems running smoothly.

Build and ship AI/LLM-assisted features in Ruby on Rails: integrate LLM APIs, implement retrieval/context patterns, ensure reliability, tests, fallbacks, and production safeguards, and maintain system performance, security, and accuracy.

Develop and deploy AI features for a SaaS product, architect scalable backends, optimize vector databases, and manage Azure AI infrastructure.

The Product Manager - AI will define AI product direction, collaborate with engineering, and solve complex user problems in payroll and compliance workflows.

Join the Jimdo AI team to architect and build the Companion system, integrating AI to assist microbusiness owners in various business tasks and workflows while ensuring system intelligence improvements and architectural scalability.

As a Principal AI Researcher, you will lead AI research projects, mentor teams, and implement innovative AI technologies for Veracode's products.

The Principal Product Manager will define the vision and strategy for the Elastic Agent Builder, guiding product execution in AI agents using advanced technologies. Responsibilities include collaborating with customers, managing product roadmaps, and leading teams to enhance AI capabilities and user experiences.

Lead technical initiatives for Generative AI in logistics, design architecture, implement evaluation pipelines, and mentor engineers.

The role involves developing sophisticated LLM-powered autonomous agents, integrating intelligent services, and ensuring systems' scalability and reliability. Responsibilities include architecting AI modules, leading agile sprints, and monitoring production lifecycle with CI/CD roles.

Design multi-turn prompts to test personalization, evaluate and rank model responses for grounding, integration, and helpfulness, write clear rationales, extract debug info, and clear sessions. Work independently in a remote, full-time contractor role with required daily PST overlap.

As an AI Engineer, you'll design AI tools for authors, enhance internal workflows, and build tools for AI development, collaborating with teams to identify AI opportunities.

The Senior AI & Computer Vision Software Engineer will work on innovative software solutions, bridge research and production, and mentor others while working in an Agile environment.

Design, implement, and run automated benchmarking and validation pipelines for AI-driven genomic interpretation. Expand regression datasets, execute large-scale validation across curated VCFs, surface accuracy regressions, build automated QA for AI releases, and integrate validation into CI/CD with dashboards and documented failure modes.

Lead evaluation and benchmarking of AI-driven genomic interpretation: own gene/disease/variant mapping logic, define accuracy and release criteria, establish regression standards, partner on automated validation, and guide where deterministic logic supplements models.

Design, build, evaluate, and deploy LLM-driven features and AI systems. Collaborate with engineering and product teams to implement RAG, monitoring, CI/CD, and scalable cloud ML deployments while continuously improving model performance.