Top Artificial Intelligence Jobs in Spain

Design and deploy AI solutions, agent workflows, and integrations for Revenue and Go-To-Market teams. Collaborate with business experts to identify automation opportunities, build prototypes, and scale successful solutions with central AI infrastructure teams. Drive AI adoption, contribute to the roadmap, and ensure technology delivers measurable business outcomes across sales operations.

Advise C-level life sciences and healthcare executives on AI and data strategies, lead large-scale digital transformations, develop client solutions, and guide implementation and scaling. Build new business opportunities, manage long-term client relationships and multimillion-dollar portfolios, lead cross-functional engagement teams, and ensure high-quality analytical deliverables. Contribute to practice development and organizational growth.

Lead discovery, design and delivery of Big Data and AI products for internal Kyivstar teams. Engage stakeholders, define vision, prioritize roadmaps, manage PoCs/MVPs to production, coordinate data and engineering teams, run pilots and measure business impact to ensure solutions create measurable value.

Design, build and deploy production-grade agentic AI systems and LLM/RAG features. Own multi-agent orchestration, prompt engineering, evaluation, and full ML lifecycle from training pipelines to online inference and monitoring. Improve ML platform and tooling (MLflow, Airflow, SageMaker, Kubernetes), collaborate cross-functionally, and lead research on advanced RAG, graph representations, and agentic evaluation.

Lead an international engineering team to design, implement, and deploy ML/Generative AI/vision systems (including LLMs, RAG, agentic AI) into cloud production. Manage project scope, risks, timelines, stakeholder communication, and technical direction while ensuring quality, documentation, and cross-team collaboration.

The Backend Engineer will develop and maintain features for Restream web services, design backend APIs, ensure infrastructure resilience, and contribute to a collaborative team environment.

PhD-level research intern to investigate and prototype 3D computer vision methods (SLAM, VIO, localisation, reconstruction). Survey SOTA, design and benchmark algorithms under real-world conditions, convert ideas into prototypes, and report results to a distributed European team focused on deployable defence-grade spatial perception.

Own and implement the engineering and integration layer for AI capabilities, prototype LLM/RAG pipelines, build APIs and pipelines, integrate AI into CI/CD and observability platforms, ensure security/compliance and traceability, and drive automation and developer productivity in cross-functional teams.

Embed with customers to prototype, build, and ship production-grade AI and agentic applications; advise on AI strategy and deployment; codify repeatable architectures and playbooks; implement LLMOps/MLOps practices (RAG, fine-tuning, semantic search, observability); mentor teams and feed product improvements.

Senior full-stack engineer building AI-powered digital products. Work across full-stack environments using TypeScript and React, leverage AI tools and LLMs, design agent-based integrations, collaborate cross-functionally, adapt to shifting priorities in fast-paced teams.

The Growth Automation Manager will build and scale Tendios' outbound automation system, focusing on creating a signal-driven opportunity activation engine for public procurement, managing outreach tools, and utilizing AI for personalization. Responsibilities include designing workflows, optimizing messaging, and measuring performance based on generated pipeline and revenue outcomes.

Senior technical lead embedding with customer teams to design, architect, and deliver production-grade AI/ML solutions. Drive model optimization, high-performance training (TPUs), efficient serving (vLLM), MLOps, agentic systems, GDPR-compliant private AI, ROI and cost optimization, pre-sales technical support, mentoring, and external thought leadership.

Build and maintain the marketing automation backbone and AI agent integrations. Implement event tracking, data pipelines, CRM customizations, and cross-channel workflows. Prototype agent infrastructure, connect APIs/webhooks, automate go-to-market tasks, and produce analytics and attribution to support growth and experimentation.

Build production agent logic, tools, and orchestration; implement RAG pipelines (ingestion, embeddings, retrieval, re-ranking); design Postgres schemas and vector indexes; build test-generation/execution engines; integrate with Git and CI/CD; ensure reliability, observability, and safety; write typed, well-tested Python.

Build and ship secure, production-ready CI/CD and AI-integrated features end-to-end. Design, implement, and iterate on products (e.g., hardened GitHub Actions, agent features), work closely with Product and front-end teams, make architectural decisions, and extend Chainguard's agentic AI capabilities into customer-facing experiences.

Serve as the bridge between engineering and business to deliver AI products from PoC to production. Translate business needs into product requirements, manage planning and prioritization, challenge technical decisions for scalability, mitigate risks and dependencies, and maintain stakeholder alignment and delivery cadence across cross-functional teams.

The AI Specialist responds to customer inquiries, troubleshoots tech issues related to AI, and collaborates with teams for client satisfaction.

Design, prototype, and deploy state-of-the-art multimodal neural search and ranking deep learning models for personalized learning; collaborate with product and engineering, mentor junior scientists, and establish ML best practices and production pipelines.

Lead development and deployment of deep learning, NLP, and multimodal AI models for personalized learning and AI tutors. Drive research, prototype solutions, collaborate with product and engineering teams, and mentor junior scientists while ensuring scalable production pipelines and ML best practices.

Design and implement user-facing features from concept through implementation, combining UX design and front-end engineering. Build, iterate, and maintain UI/UX and business logic to drive engagement and conversion, collaborate with product/marketing/support, participate in code reviews, and leverage modern tools and deployment workflows.

Design and evolve an enterprise-scale, model-agnostic Agentic AI platform: agent runtime, orchestration, context/memory, evaluation, guardrails, observability, governance, and integrations. Define golden paths, build an Agent Harness and runtime supporting multiple LLM providers, collaborate on Kubernetes/GPU/cloud infra, and drive developer standards and enterprise adoption.

This role involves designing, developing, and deploying AI and automation solutions, ensuring integration with enterprise systems, and meeting security standards. The position requires hands-on engineering skills in AI development, particularly with Python and AI frameworks.

The Lead Software Engineer will develop AI-powered software, focusing on backend systems, APIs, microservices, and collaborating in agile teams to deliver technical solutions.

The Lead Software Engineer will develop AI-powered software solutions, design backend systems, and collaborate with cross-functional teams to enhance AI capabilities.

Develop and maintain open-source, silicon-optimized AI/ML inference application packages (Inference Snaps) for Linux/Ubuntu Core. Debug, write high-quality code, review upstream contributions, secure and optimize local inference deployments across embedded devices to gateways, and collaborate with a distributed team and stakeholders.