Top Artificial Intelligence Jobs in Barcelona

As an AI Engineer, you will build AI agents for preventive health, focusing on reasoning, clinical workflows, and ensuring reliable production systems.

As a Senior AI Product Manager, you will own the AI Travel Agent product, leading the full post-booking servicing scope while collaborating with engineering and customer success on product discovery and delivery.

Join the AI Engineering team to design, build, deploy, and scale production AI systems. Translate business problems into AI solutions, industrialize ML models, design AI pipelines and platforms, ensure performance and monitoring, and drive MLOps best practices across architecture and governance.

This role involves managing Microsoft Commercial Marketplace integrations, evaluating opportunities, conducting feasibility assessments, and leading R&D for novel API integrations and enhancements.

Design, develop, deploy, and maintain scalable AI/ML systems and pipelines. Apply MLOps/LLMOps/AgentOps best practices, run large-scale experiments, build engineering infrastructure for batch and real-time workflows, and integrate models into business applications with monitoring and APIs. Collaborate with scientists, engineers, and product teams to deliver end-to-end solutions using Python, MLflow, Azure, and Databricks.

Operate and improve the Guardicore Data & AI Platform for reliability, availability, performance, and security. Manage Kubernetes infrastructure, observability, CI/CD, and IaC; lead production investigations, automate remediation with AI/LLMs, partner across engineering teams, and participate in on-call rotations.

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.

Provide research and advisory to global CFOs and Controllers on transforming controllership processes (AP, AR, financial close) using AI, automation and finance technologies; produce published research, vendor evaluations, and client-facing presentations; collaborate with analysts and deliver strategic, actionable recommendations to improve financial reporting and automation outcomes.

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.

Lead engineering enablement across eight companies to cascade CTO AI vision into team discipline. Detect and package successful practices, run cross-company diffusion, operate cadence of validation and demos, measure adoption and outcomes, triage deeper needs to PoCs/workshops, and capture reusable artifacts and metrics.

As a Staff/Senior AI Product Engineer, you will build AI-powered product features, enhance the tech stack, and design AI workflows while collaborating with product teams. Your focus will be on agent-native architecture and improving the codebase for AI agents.

Design and build LLM-powered tools, agents, and automations to streamline internal processes across teams. Scope, implement, integrate, and ship agents and automations (LLMs, RAG, tool use) with measurable productivity metrics, integrating with systems like Slack, Ashby, and BigQuery.

As a Senior AI/ML Engineer, you will develop and deploy AI initiatives, focusing on ML solutions and ensuring robust software integration. Responsibilities include coding, MLOps implementation, Agile delivery, and collaboration with stakeholders to translate business needs into technical solutions.

As an AI Machine Learning Engineer, you'll develop and deploy AI solutions, implement MLOps workflows, and partner with stakeholders to translate business challenges into technical requirements.

Lead AI engineering initiatives by establishing platform strategies, managing talent, enforcing technical standards, and ensuring the operational excellence of AI products.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

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.

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.

Design polished, user-centric mobile and web interfaces for BJAK's AI-driven financial products. Create wireframes, flows, prototypes and high-fidelity UI, evolve the design system, collaborate with product and engineering, iterate from user feedback and analytics, and ensure accessibility, responsiveness and visual consistency across devices.

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

Lead an enterprise AI product pod to define use cases, KPIs, scope, and adoption; coordinate cross-functional stakeholders (Legal, Quality, IT/Security); ship LLM/agent/RAG solutions into real workflows; produce reusable Fabric assets; manage roadmap, telemetry-driven adoption, and portfolio reporting.

Build domain data products and pipelines for AI consumption: create retrieval-ready, semantically annotated, contract-governed assets; deploy agents for metadata, entity resolution and classification; ensure data quality, lineage, certification, and reuse; collaborate with domain stewards, business teams and IT to model, store and serve structured and unstructured data for retrieval and modeling.

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.