Senior AI-Native Developer

There are NO limits to your career: come shape the future and be part of a truly unique global culture at OutSystems! About the OutSystems Digital Team We are the digital backbone of OutSystems' growth — building the enterprise applications, integrations, and AI agents that accelerate the company into the AI-powered era. We work in small, high-autonomy teams of two to five people, each with full AI tooling, a clear mission, and the authority to ship. The Role You will join an existing team and take technical ownership of a portfolio of live products and SaaS, while spending most of your energy building new things that did not exist before. The balance we aim for is roughly seventy percent innovation — new agents, new integrations, new capabilities — and thirty percent maintaining and evolving what is already running. That split is a principle, not a rigid rule: when a live system needs attention, you give it. What stays constant is that you own your output end to end, whether it is new or existing. The binding constraint on what you produce is no longer typing speed. It is judgment — your ability to direct AI tools toward correct, production-ready output, validate what comes back, and iterate with precision. What You Will Own Features and integrations that ship to production — real users, real consequences, and your name on them Quality of AI-generated code before it merges — you develop the instinct to distinguish correct from plausible, and you apply it before anything reaches production LLM integrations that hold under real conditions — connecting Claude, GPT, or other models via OutSystems' secure API gateway in a way that works in production, not just in demos AI agents built on OutSystems Agent Workbench that run unsupervised on real enterprise workflows and produce output that is trustworthy, not just impressive Your share of the existing portfolio — understanding the applications the team maintains well enough to extend them without accumulating hidden debt Shared context that makes the whole team faster — documenting decisions and patterns so that the team's AI tools operate with full enterprise context; treating documentation as compound interest The Behaviors We Are Looking For We care less about which tools you know today and more about how you work. This is what we are actually evaluating: You build first and sharpen later . Given a rough brief, you start building and let requirements clarify through iteration. You do not wait for a complete specification before producing something real. You distinguish correct from plausible. You have used AI tools enough to know that output which looks right is not always right. You have caught the difference and you apply that instinct before anything ships. You own what you ship . You do not hand something off and move on. You care whether it works in production, whether it holds under load, whether it solves the actual problem — including in systems you inherited rather than built. You find a way around walls. When you hit a blocker, you try before you ask. When you do ask, you arrive with what you have already tried and what you have already ruled out. You share context generously. In a small team, what you know is a shared asset. You document, you flag assumptions, you explain your reasoning. You understand that a well-contextualized AI tool produces better output for everyone, not just for you. You are honest about what you do not know . In a team of five, a gap in understanding that goes undeclared becomes a gap in the product. You surface uncertainty rather than hiding it behind confident-sounding output. Experience 3+ years of development experience, with depth in at least one area — integration, data, UI — and genuine curiosity across others Active practitioner of AI-augmented development — you use Claude, Cursor, Copilot, or similar tools as a core part of how you build, not as an occasional shortcut Strong integration fundamentals: REST APIs, JSON, authentication patterns, error handling under real conditions Comfortable producing something from a rough brief and sharpening it through iteration Bonus Experience with OutSystems Mentor or AI Agent Builder Familiarity with prompt engineering patterns and LLM context window management Prior experience in a high-autonomy environment where every person's output is visible and tested daily Domain knowledge in finance, insurance, healthcare, or logistics This Is Not For You If... You treat AI tools as an occasional shortcut rather than the primary way you build Ambiguity stalls you — you need complete requirements before you can start You consider maintaining and evolving existing systems to be below your level You have never caught an AI tool producing output that looked right but wasn't — or you have, and it did not change how carefully you review You prefer to discuss what to build over shipping something testable and learning from it Growth Path High performers in this role move into technical leadership within 12 to 18 months, or into specialist roles in AI agent design or enterprise context engineering — disciplines that barely existed two years ago and are among the highest-leverage skills in the industry today. We will show you who has already made that move. Why Join The skills you will develop here — context engineering, AI agent validation, enterprise-grade agentic development — are not in any curriculum. You will learn them by applying them in production, on real systems, alongside people who are figuring them out at the same frontier. If you want to be one of the first people in the industry who actually knows how this works — not in theory, but in production — this is where you do it. More about OutSystems OutSystems is a leading AI Development Platform built for the enterprise. Global organizations trust OutSystems to rapidly build mission-critical apps and agents, modernize l