Top Artificial Intelligence Jobs in Seville

Build and improve Restream’s web interfaces and user-facing features for the AI Clips team. Design UI and business logic, collaborate with product designers, participate in code reviews, improve system reliability, and evaluate emerging technologies. The role requires strong JavaScript and TypeScript expertise, advanced React knowledge, CSS preprocessor experience, and familiarity with backend development, cloud infrastructure, containers, and continuous deployment.

Join the AI & Innovation team to build and maintain full‑stack Python services, integrate ML/LLM models into production, develop scalable APIs and data pipelines, optimise AWS infrastructure, and write unit/integration tests to ensure reliability for high‑traffic jobseeking products.

Lead enterprise AI strategy, operating model, governance, platform enablement, and CoE to deploy safe, compliant, and scalable AI across R&D, Clinical, Manufacturing, Quality, Commercial, and Corporate functions in a regulated pharmaceutical environment.

Create high-volume, high-quality marketing content using generative AI and AI agents. Produce video, image, and social content, develop attention-driving campaigns, track AI and culture trends, and iterate quickly with the marketing and founding team.

Build features, prototypes, and demos using modern AI coding tools and agents; iterate prototypes into reliable, scalable production; direct and evaluate AI coding agents; collaborate closely with founders and senior engineers; explore and improve AI development workflows to accelerate product delivery.

Lead AI-native engineering: build and ship production-grade features, convert AI-assisted prototypes into reliable systems, own architecture/security/quality, direct AI coding agents, define engineering standards, and work closely with founders on product and technical strategy.

Lead design and ownership of shared libraries, Spring Boot starters, and agentic frameworks. Set standards for agent orchestration, evaluations, and guardrails. Mentor teams on Python-based agents (LangChain/LangGraph), drive adoption, prototype research directions, and improve developer experience across Kotlin backend and client libraries.

Provide EU-focused counsel on AI and privacy regulation (EU AI Act, GDPR, DSA); draft policies, DPA and contractual terms; translate legal requirements into technical and operational controls; advise product, engineering, and go-to-market teams; liaise with regulators and manage compliance programs and risk assessments.

Develop and maintain front-end and back-end AI-enabled web and desktop applications. Collaborate with cross-functional teams to design features, optimize scalability and security, troubleshoot defects, participate in code reviews, and implement AI assistant technology integrated with enterprise systems.

Architect and build production AI-powered HR systems using agentic workflows, multi-agent systems, APIs, and workflow automation. Integrate Workday and other HR tools, implement governance, audit logging, privacy controls, and human approval gates, and ensure reliable payroll-adjacent workflows. Document solutions, train People team users, drive adoption, and measure automation impact. The role requires strong software engineering, AI application development, HR technology, Workday, data privacy, and workflow automation experience.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

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.

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.

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, 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.