Staff AI Engineer - API & Integrations Team (Madrid)

Hello! Do you want to help us redefine how AI powers the future of Business Management software, not as an add-on, but as a core part of how people work, decide and grow ? We’re looking for engineers who: Treat AI as central to their craft, not a feature to bolt on later Want to build and ship, not debate and document Care about whether the thing they built actually worked — not what their title says. Ready to be part of the challenge? 🚀

About

the team 👥 Our Engineering team is the engine behind Factorial, crafting the tech that makes HR simple, fast, and reliable for thousands of companies. If you love solving hard problems and want to build something that truly matters, come build it with us. We're a team of 200+ Product Engineers building Business Management solution that actually works for the people using it. Our core stack is Ruby on Rails and React but the interesting work right now is what we're building on top of that: agentic workflows, LLM-integrated features, systems that behave probabilistically rather than deterministically. The API & Integrations team addresses particular challenges at Factorial. We sit at the intersection between product and platform. We own product surface while we also design developer experiences for internal and external developers of integrations. We build tools for Factorial product teams to publish in our extensive public API . We build an integrations framework to achieve the best user experience and developer experience when using integrations. Several factorial products are already using this framework. And we keep expanding it. We enable our developer partners to extend Factorial and live the best developer experience. With the acquisition of YepCode , we will be boosting how we build integrations, placing AI at the center of the process. Our mission is not only to unblock markets that rely on a fragmented market of different external software (payroll software solutions, ERPs, cloud-based identity services, etc.), but also to lower the barrier so that anybody (even HR managers) is able to create new integrations. What You’ll Do 🚀 As a Product AI Engineer at Factorial, you’ll help define and build the next generation of our AI-native product using modern AI development practices . You will: Build product using Spec Driven Development We define clear specifications before shipping — including expected behaviours, constraints, and success criteria — and use them to guide implementation, iteration and evaluation using most powerful LLMs. Design and implement AI Skills Create reusable, well-scoped AI capabilities that can automate and take actions safely within Factorial’s workflows, and also when building integrations Develop and maintain evaluation frameworks (Evals) Measure quality, correctness and reliability of AI outputs using automated and human-in-the-loop evaluations to ensure continuous improvement in production. Apply Retrieval-Augmented Generation (RAG) Build systems that ground AI responses in trusted, up-to-date company data, balancing probabilistic models with deterministic sources of truth. Design human-in-the-loop and agentic workflows Combine LLMs, rules, and user oversight to automate real business processes while keeping humans in control of critical decisions. Own systems end-to-end From problem definition and system design to shipping, monitoring and iteration in production. Stay close to our customers We have a strong customer-centric mindset : engineers regularly join customer calls, reviews, and feedback sessions to deeply understand real workflows, pain points, and constraints — ensuring we build the right solutions to real problems , not assumptions. Collaborate closely with Product and Design Shape how AI is embedded into core user experiences — not as a feature, but as part of the workflow. Share knowledge and raise the bar Mentor peers, document learnings, and contribute to Factorial’s AI engineering best practices. What are we looking for? 🧠 Your title matters less than your mindset . You might be mid, senior, or staff. What we care about is: AI as a habit : you’ve built real AI-powered systems or workflows (not just experiments) Proven impact : shipped projects, side projects, or contributions that made a measurable difference Product-first thinking : you design complete experiences, not just isolated components Speed & adaptability : you experiment, learn, and iterate fast