Software engineer
Indexed description
We build the digital infrastructure that helps brands understand why returns happen, reducing waste and helping the planet one return at a time. We are a small, agile team where data-driven decisions meet environmental impact.
Yayloh is a profitable growing scale-up. We are still small and lean, move like a startup. You will have creative, meaningful work with stability and work/life balance
🛠️ The Role: Backend with a Fullstack Heart
We are looking for a Master’s Graduate (M.Sc.) with a 5-year background in Computer Science or equivalent, to help build the future of sustainable retail.
While your core focus will be our Python and MySQL backend, we operate with a "get it done" mindset. This means you’ll occasionally step into our React/TypeScript frontend or even into our AWS infrastructure to ensure a seamless experience for our merchants. You aren’t just a coder; you’re a problem solver who uses the best tools available—including AI—to build elegant, scalable solutions.
💎 What We Offer
- Purpose: Work on a product that directly reduces carbon emissions and textile waste.
- Balance: 5 weeks of paid vacation to recharge.
- Future: Employee stock options – we want you to own a piece of the impact you create.
- Security: Service pension (Tjänstepension) and competitive benefits.
- Growth: A high-autonomy environment where you can influence the tech stack and product roadmap.
- Education: A recently completed Master’s degree (M.Sc.) in Computer Science or equivalent.
- Right to Work: You must currently hold the legal right to work in Sweden.
- Work from office: We need you to work from our Stockholm office with option to work from home couple of days a week if needed.
- Tech Interests: Proficiency in (or a strong desire to master) Python, MySQL, and React/TypeScript.
- Critical Thinking: The ability to look at an AI-generated solution and ask, "Is this actually efficient, or just shiny?"
In your README or commit history, you must highlight:
- AI Usage: How you used AI (Cursor, Copilot, LLMs) to build the project.
- The "Hallucination" Commit: Link to at least one specific commit where the AI failed—either by suggesting a "Rube Goldberg" solution (too complex) or by hallucinating a library/logic.
- The Fix: Show us how you caught the error and how you simplified or corrected the code in the followup commits.
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