Software Engineer
Lead technical ownership of live AI‑powered products, building innovative enterprise applications and integrations on the OutSystems platform. Focus on Python‑based ML, AI tooling, and SaaS delivery to accelerate the company into the AI‑powered era.
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 mov
Posted June 27, 2026