Top Artificial Intelligence Jobs in Madrid

Own reliability, availability, performance, and operational readiness of a cloud-native data and AI platform. Operate Kubernetes infrastructure, improve observability, security, performance and cost efficiency, lead production investigations, use AI/LLMs for automation, collaborate across DevOps, Software, Data and Security 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.

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.

Plan and execute AI-assisted red team engagements across web apps, APIs, cloud and infrastructure. Deliver prioritized reports, validate fixes, tune offensive tooling, automate playbooks, integrate security into CI/CD, run remediation workshops, and coordinate triage with SOC and product teams.

Lead and execute AI-assisted red team engagements across web apps, APIs, cloud workloads and infrastructure. Manage two direct reports, integrate security into CI/CD, tune offensive tooling, run remediation workshops, coordinate with SOC/IT Ops, and deliver prioritized technical and executive reports.

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, build, and deploy production-grade agentic AI systems at enterprise scale. Lead client engineering engagements, define RAG and multi-LLM standards, own LLMOps and eval harnesses, establish observability, safety, and cost controls, and publish reusable patterns and metrics to demonstrate business impact.

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, build, and run production agentic workflows and reusable components for delivery processes. Implement RAG-backed knowledge bases, monitoring, evals, observability, and human-in-the-loop feedback to improve agents and integrate them with delivery teams and business tools.

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.

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.

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.

Lead development and scaling of AI-powered clinical applications using LLMs. Gather user and industry requirements, write product specifications, prioritize roadmaps, coordinate sprints and releases, validate quality with engineering and QA, and design generative AI capabilities to streamline pharmaceutical workflows and regulatory documentation.

Design, build, and improve ML models and production pipelines; collaborate with engineers, data scientists, and PMs; develop experimentation roadmaps; set up reproducible environments; monitor and maintain production models; document models and processes; propose and apply new AI/ML solutions.

Own the end-to-end customer-facing conversational agent across chat and voice. Lead roadmap, conversation and interface design, partner discovery and onboarding, prototyping, quality metrics, and agent behavior specification. Work hands-on in Figma, build prototypes with AI coding tools, and iterate from production data with cross-functional GTM and success teams.

Build end-to-end AI-native product features across frontend, backend, and LLM integrations. Design and deploy agent workflows, streaming real-time interactions, memory, and tool integrations. Improve reliability, observability, fallbacks, and reduce latency while collaborating with ML and product teams to ship production-grade, multi-step workflow capabilities.

Build and ship end-to-end AI features: design prompts, tools, memory, and agent workflows; turn model outputs into reliable behavior; debug across model, orchestration, infra, and UX; optimize latency, cost, and reliability; develop evaluation frameworks and collaborate with product and engineering to deliver robust ML-powered features.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.