Full Stack Engineer

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Full Stack Engineer based in Spain. As a Full Stack Engineer – AI Systems, you will build production-ready AI applications that transform how people manage their emails, calendars, notes, and everyday tasks. You will work at the intersection of full-stack engineering and advanced artificial intelligence, developing intelligent agents that deliver seamless, proactive, and intuitive user experiences. Your responsibilities will span frontend and backend development, large language model (LLM) integrations, and sophisticated agentic workflows. You will design systems capable of planning, using tools, retaining context across sessions, and recovering gracefully from unexpected failures. Working alongside experienced engineers and machine learning specialists, you will help establish scalable architectures and reliable AI integration patterns. With a strong focus on performance, low latency, and user trust, you will turn emerging AI capabilities into practical features ready for real-world use. This fully remote opportunity offers significant technical ownership, a greenfield product environment, and the chance to shape the future of AI-powered productivity.

Build end-to-end product features: Develop and maintain full-stack functionality across frontend interfaces, backend services, and AI integrations, ensuring a seamless user experience. Design intelligent agent workflows: Create multi-step agentic systems capable of planning, executing tasks, interacting with tools, handling failures, and recovering across multiple sessions. Integrate AI technologies: Connect large language models, memory architectures, retrieval-augmented generation (RAG) systems, and external APIs to deliver reliable, context-aware application experiences. Develop real-time user experiences: Architect interfaces that support streaming responses, partial results, responsive interactions, and strict latency requirements. Ensure system reliability: Improve observability, monitoring, error handling, fallback mechanisms, and recovery strategies to maintain dependable AI-driven functionality. Evaluate and improve AI performance: Collect and analyze user feedback, behavioral signals, and telemetry to support model evaluation, reduce hallucinations, and guide continuous product improvements. Design scalable architectures: Collaborate with machine learning and backend engineering teams to establish robust system designs, API structures, and reusable integration patterns. Drive features from concept to production: Take ownership of technical implementation, make independent engineering decisions, and deliver high-quality solutions in an evolving product environment. Champion user-centric engineering: Apply strong product judgment to ensure AI-powered features remain intuitive, resilient to unpredictable model behavior, and useful in everyday scenarios. Requirements: Full-stack development experience: Strong professional experience building applications with modern technologies and frameworks, particularly Next.js, Python, and Node.js. Practical AI engineering expertise: Hands-on experience developing AI-powered applications, implementing RAG systems, or integrating LLM APIs from providers such as OpenAI, Anthropic, or open-source model ecosystems. System design and architecture: Solid understanding of application architecture, API design, distributed systems concepts, and database technologies, including SQL and NoSQL. Reliable AI application development: Demonstrated ability to design robust user experiences that account for network latency, non-deterministic model outputs, graceful degradation, and unexpected failures. DevOps and cloud infrastructure: Experience with containerization, deployment pipelines, and cloud orchestration technologies such as Docker and Kubernetes. Problem-solving and adaptability: Ability to navigate ambiguity, evaluate technical trade-offs, exercise independent judgment, and solve complex engineering challenges. End-to-end ownership: Proven ability to take features from initial concept through development, deployment, and ongoing optimization. Strong product intuition: A user-focused mindset with particular attention to client-side reliability, usability, responsiveness, and the practical value of AI-driven features. Collaboration and communication: Ability to work effectively with cross-functional engineering and machine learning teams while contributing to technical decisions and scalable product development. Location and remote readiness: Based in the Netherlands, with the ability to collaborate effectively within a fully remote, international team. Benefits: Fully remote work: Flexibility to work remotely as part of a globally distributed team. Competitive compensation: Flexible compensation arrangements designed to attract experienced engineering talent. Equity participation: Significant equity opportunities, allowing you to share in the potential long-term success of the product. High-caliber colleagues: Work alongside experienced engineers from leading technology companies in a technically ambitious environment. Greenfield product development: Help build an AI-powered productivity platform from the ground up, with opportunities to influence architecture, engineering standards, and product direction. High-impact ownership: Take responsibility for meaningful technical initiatives and see the direct impact of your work on product capabilities. Advanced AI challenges: Work with agentic workflows, LLM orchestration, long-term memory, real-time streaming, and production-grade AI systems. Collaborative engineering culture: Join a small, highly skilled team that values technical excellence, autonomy, and practical innovation. Professional growth: Expand your expertise at the intersection of full-stack engineering, AI infrastructure, and intelligent product development.