Senior AI-Native Developer

External

Outsystems · Portugal

Full-timeRemoteToday

API GatewayDocumentationLessMovePrompt EngineeringREST

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About 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.

Responsibilities

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.

Senior AI-Native Developer

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