AI Engineer
The AI Engineer will design and implement Generative AI solutions, including intelligent agents and APIs. They will also manage data pipelines and deploy scalable solutions within a cloud environment using clean architecture principles.
85 AI Engineer jobs in Spain available for remote work from home. Apply for positions such as AI Engineer, AI Engineer, Senior Full Stack Engineer (AI & GenAI) | Python, React, AWS and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The AI Engineer will design and implement Generative AI solutions, including intelligent agents and APIs. They will also manage data pipelines and deploy scalable solutions within a cloud environment using clean architecture principles.
Design and build data pipelines and infrastructure to transform raw data into high-signal training sets for AI agents. Develop and optimize ML systems focusing on retrieval, ranking, and structured extraction to improve agent behavior and reliability.
Design and develop end-to-end web applications while integrating Generative AI components and managing data pipelines. Collaborate with multidisciplinary teams to ensure application security, scalability, and performance within AWS cloud environments.
You will be responsible for the end-to-end development of AI-driven applications, including frontend, backend, and cloud deployment. You will collaborate with AI engineering teams to integrate LLMs, RAG, and agentic AI into strategic cybersecurity and infrastructure initiatives.
Design and develop GenAI capabilities, including RAG architectures, agent workflows, and semantic search systems. Collaborate with cross-functional teams to integrate AI models into business applications while ensuring performance, security, and scalability.
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Design, develop, and implement scalable Generative AI solutions using Python and LLMs. Manage cloud infrastructure as code and integrate AI components into productive environments.
You will design and deploy agent-based AI systems by integrating language models with internal and external tools to solve complex business problems. You will take end-to-end ownership of the AI lifecycle, from discovery and prototyping to production monitoring, evaluation, and scaling.
Lead the company's digital transformation by implementing intelligent process automation and Generative AI solutions. Design, build, and deploy agent-based systems and workflow automations to improve organizational efficiency and productivity.
You will design, build, and optimize agentic AI systems to automate complex procurement workflows. Your work will involve integrating and fine-tuning LLMs to drive intelligent decision-making across the platform.
Design and develop applications based on LLMs and GenAI while building RAG and GraphRAG systems to extract knowledge from large datasets. Implement advanced AI agents, scalable backend APIs, and data pipelines to support business needs in an Agile environment.
Design and develop CFD and aerodynamics tasks to evaluate AI model engineering reasoning. Create deterministic scoring checkers and verified reference solutions to ensure technical accuracy of AI-generated responses.
Design and develop advanced AI solutions based on LLMs, including synthetic AI personas and insight generation tools. Build scalable backend services, data pipelines, and integrations to support decision-making in the pharmaceutical sector.
Collaborate on the design and implementation of innovative AI-based solutions to meet project requirements. Optimize existing machine learning models for performance and scalability while contributing to technical documentation.
Develop and deploy scalable Conversational AI solutions, including chatbots and voicebots, using LLMs and Agentic AI. Define technical architecture and manage integrations with enterprise systems, CRMs, and telephony infrastructure.
Own and scale the agent layer and matching engine for an AI-first fundraising platform. This includes building conversational agents for investor outreach and managing the backend data pipelines.
Own the conversation layer of an AI fundraising platform, managing agents that handle replies, booking, and relationship nurture. Build broader applied-AI features including classification, extraction, and the evaluation framework to ensure quality.
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Develop and optimize ML models from scratch while collaborating with cross-functional teams to deploy them into production. Establish experimentation roadmaps and maintain reproducible pipelines to ensure optimal model performance.
Design and implement AI/ML solutions and Agentic AI architectures using Vertex AI and Gemini Enterprise on GCP. Manage data platforms, automate infrastructure with Terraform, and maintain MLOps pipelines in Kubernetes environments.
Own and drive the quality, reliability, and evolution of production AI systems, including the delivery of major AI features. Design and orchestrate agentic, tool-using AI workflows and manage prompt engineering and experimentation pipelines.
Design and implement AI solution architectures, including APIs and data extraction/transformation pipelines using Python. Act as a technical interlocutor for clients and deploy scalable solutions in the cloud following clean architecture patterns.
Design, train, and validate machine learning and deep learning models for clustering, classification, and anomaly detection. Integrate these models into production pipelines and collaborate on cloud-based proofs of concept and technical documentation.
Design and develop AI-powered features and agentic workflows to help users analyze large datasets. Take ownership of the full development lifecycle from rapid prototyping to shipping scalable production-grade solutions.
Develop and modernize applications using Artificial Intelligence and implement intelligent automations. Design and manage agent-based workflows while collaborating with multidisciplinary teams to integrate AI into business processes.
Design and develop production-grade AI services, agentic frameworks, and large-scale retrieval systems to power intelligent automation. Collaborate with cross-functional teams to implement scalable AI orchestration and observability frameworks across the enterprise ecosystem.
Design and develop Generative AI applications using LLMs, Agentic AI, and GraphRAG to transform business and scientific data into actionable insights. Build scalable backend services, APIs, and data pipelines within an Agile environment.
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Design and implement advanced Generative AI solutions, including corporate assistants and custom agents, within the Google ecosystem. Integrate Gemini with corporate applications via APIs and design architectures on Google Cloud Platform to automate internal processes.
Develop production-ready coding agents and agentic workflows by integrating internal and open-weight models into JetBrains products. Design the agent loop, create evaluation suites, and establish feedback loops to improve model behavior based on real-world usage.
Develop autonomous AI agents capable of financial decision-making and task execution. Build and integrate REST APIs and agentic workflows using LLMs and emerging communication protocols.
Design and implement intelligent conversational agents using agent-based architectures and LLMs. Integrate these agents with corporate systems, REST APIs, and cloud environments like GCP Vertex AI while ensuring scalability and quality.
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