Top Artificial Intelligence Jobs in Spain

Own AI cost visibility features end-to-end, from customer problem discovery and system design through implementation, release, monitoring, and iteration. Build scalable Go backend services, APIs, and TypeScript/React interfaces that process and present cloud AI spend data. Apply AI throughout the engineering workflow, contribute to product direction, understand FinOps and AI economics, mentor peers, and uphold reliable engineering practices.

Owns enterprise customer engagements from requirements discovery through implementation, adoption, relationship management, and renewal support. Translates ambiguous financial-services problems into measurable AI-powered workflows, manages delivery plans and governance, tracks usage and account health, measures ROI, and communicates risks. Builds senior client relationships while partnering with Product and Engineering to incorporate feedback and improve solutions.

As a Lead AI Deployment Architect, you'll design, deploy, and scale AI solutions using Celonis' Process Intelligence platform, collaborating with customers and internal teams to align solutions with business strategies.

Design and deliver production-ready enterprise AI systems using LLMs, retrieval-augmented generation, agentic workflows, and cloud-native services. Lead architecture, prototyping, evaluation, monitoring, deployment, and continuous improvement while mentoring engineers and shaping AI strategy. Collaborate with customers, product teams, architects, and domain experts to translate business needs into scalable solutions and measurable outcomes.

Lead commercialization of AI oncology products (especially MEDULAI) by identifying partners, designing business and market access strategies, negotiating commercial and data agreements, promoting digital pathology solutions, and aligning internal teams to market needs.

Leads pre-sales architecture for enterprise AI and data solutions centered on Salesforce Data Cloud and Agentforce. Designs integrations with hyperscalers, data lakes, external agents, and governance frameworks; builds prototypes, demos, and prompt lifecycle strategies; facilitates customer workshops; and develops technical enablement content. Advises on data modeling, identity resolution, agent interoperability, observability, and activation patterns while supporting early post-sale adoption.

Owns the end-to-end computer vision core of an industrial visual inspection product on NVIDIA hardware. Designs unsupervised anomaly detection and supervised defect segmentation models, optimizes GPU inference with CUDA and TensorRT, and develops real-time C++ pipelines. Manages model versioning, dataset curation, monitoring, drift detection, retraining, and rollback. Requires expert Python, PyTorch, modern C++, production MLOps, and latency-focused systems engineering in a fully remote environment.

Staff AI Engineer in dLocal’s AI Lab responsible for scouting, prototyping, benchmarking, and evaluating emerging AI technologies. Builds evaluation harnesses and experimental systems for LLMs, agents, retrieval, and orchestration; assesses quality, cost, latency, security, and reliability; and produces adoption recommendations. Defines guardrails and readiness guidance, coordinates production hand-offs, supports governance, mentors engineers, and communicates findings to technical and non-technical stakeholders.

Build, operate, and improve production services that deliver machine learning models within exocad’s AI Design product. Responsibilities include model serving APIs, containerized deployments, versioning, staged rollouts, rollback automation, infrastructure provisioning with Terraform and AWS, monitoring, observability, and performance tuning. The role also contributes to training and labeling infrastructure and requires collaboration across engineering, product, and global teams, including work across AWS global and China environments.

Build and operate reliable full-stack DevTools and AI reliability software using Vue.js, TypeScript, Node.js, Golang, PostgreSQL, ClickHouse, and AWS. Use AI coding agents throughout development, engage directly with developer and SRE customers, identify and solve reliability problems, own features from discovery through production, and participate in support and on-call rotations within a remote async-first team.

Grow Qure’s user base from scratch by testing acquisition channels, managing budgets, creating marketing assets, building measurable funnels, and partnering with product on activation-focused improvements. The role requires rapid experimentation across paid, organic, community, video, and content channels, using data to optimize acquisition economics and eliminate underperforming efforts.

Build and enhance RAG systems, AI components, backend services, data pipelines, and REST APIs under senior guidance. Write production code, tests, evaluation harnesses, documentation, and runbooks. Support AWS deployments using containers and CI/CD, investigate model failure modes, and contribute to architectural decisions. The role offers increasing ownership while collaborating with senior engineers, FDEs, FDXs, and enterprise clients in distributed teams.

Build and operate production LLM-powered internal tools, automations, and customer-facing AI features. Own technical decisions, backend services, multi-service architectures, databases, containerized workloads, monitoring, reliability, incident response, and LLM evaluation workflows. Partner with product, security, and R&D teams while balancing AI quality, latency, and cost. Evaluate emerging AI technologies and contribute to reliable, secure production systems.

Lead workshops, architect and design Workday Extend applications, deliver requirements and design to developers, manage and guide Extend consultants, liaise with clients and Workday, and support pre-sales and AI-enabled solutioning.

Lead research and advisory on application security for enterprise applications (ERP/CRM). Produce thought leadership, client-facing insights, presentations, market analysis, and support sales. Mentor analysts, drive research agenda, improve processes, and advise CIOs on security strategy, vendor evaluation, metrics, and vulnerability testing across major vendors (SAP, Salesforce, Workday, Oracle).

Join the Orbit 12-month graduate program as an Associate Applied AI Engineer supporting customer engagements: uncover business challenges, prototype ML and LLM solutions on the Celonis Process Intelligence Platform, deliver proof projects and executive presentations, drive value realization, collaborate with product and engineering, and travel to meet clients.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Leads the design, development, maintenance, testing, troubleshooting, and optimization of complex full-stack software applications. Collaborates with cross-functional teams, documents technical requirements, resolves IT issues, prepares data, supports end users, and applies software architecture, microservices, database, CI/CD, containerization, monitoring, and Agile engineering practices.

Lead Joko’s AI Platform product tribe, owning strategy, roadmap, and delivery for Joker, Gotham, internal automation, identity, security, compliance, and reliability products. Build production-grade agent infrastructure, retire legacy tools, align stakeholders across the company, and measure efficiency, cost, risk, and adoption. The role also involves hiring, mentoring, and managing Product Managers while remaining hands-on with platform product decisions.

Manages strategic partnerships with cloud providers such as AWS and GCP. Oversees agreement execution, co-sell objectives, expense targets, partner benefits, KPI tracking, marketplace transactions, and joint go-to-market initiatives. Collaborates with sales, product, and marketing teams, resolves partnership issues, enables partner resources, and uses performance data to optimize outcomes.

Lead hands-on development of AI-powered workflows, coding-agent integrations, and C++ development capabilities for CLion. Design agent architectures, tool integrations, benchmarks, and evaluation frameworks while prototyping debugging, code understanding, refactoring, and navigation workflows. Collaborate with JetBrains AI, ML, product, QA, and C++ teams to shape technical direction, roadmap priorities, and AI strategy for developer tools.

Advise clients on becoming data-driven by assessing data and ML maturity, identifying use cases, and defining implementation roadmaps. Collaborate with data scientists, engineers, and architects on AI solutions, governance, MLOps, and analytics centers of excellence. Support business development, client relationships, conferences, sales meetings, thought leadership, and the growth of the Data & AI consulting practice.

Lead EMEA customers in deploying and optimizing large-scale AI inference on multi-node GPU clusters. Architect dense and Mixture-of-Experts inference pipelines, improve quantization, speculative decoding, prefill/decode disaggregation, KV cache management, and workload scheduling. Collaborate with NVIDIA product teams and engage the developer community through workshops, hackathons, and reference architectures. Advise ML engineers, researchers, and systems architects on high-performance inference across thousands of GPUs.

Serve as a technical bridge between NVIDIA’s generative AI platform and AI-native customers. Guide diffusion model training and deployment, optimize image and video generation pipelines across single- and multi-GPU environments, diagnose vision workload bottlenecks, and provide guidance on model architectures, inference efficiency, video tokenization, and multimodal systems. Translate customer feedback into product improvements and contribute technical demos, workshops, and reference implementations for the EMEA developer community.

Serve as the senior technical expert for EMEA AI organizations training and post-training large-scale foundation models. Advise customers on distributed training infrastructure, PyTorch, Megatron-LM, NeMo, reinforcement learning, GPU utilization, communication overlap, and memory management. Build strategic technical relationships, translate customer needs into NVIDIA product roadmap input, collaborate with research and product teams, and support hackathons, demonstrations, and technical conferences.