Senior Software Engineer

But coding is just one thing. We're a team wearing many caps . One week you could be jumping into demand forecasting or pricing recommendations, the next you're shipping task automations across domains like housekeeping, distribution, or inventory optimization - the kind of cross-domain problems where the exception-driven, AI-assisted approach really shines.

You'll also help build the tools that make your teammates' life easier: CI/CD, automation, cloud setup, internal AI workflows.

How do we manage all this work? GitHub for project management and issue tracking, Notion for knowledge base. We hate bureaucracy as much as you do.

And, of course, there's always time left to share a drink with your colleagues.

Our tech stack?

• Go and React.
• Google Cloud: Kubernetes, Cloud SQL, Pub/Sub, Cloud Storage, KMS, BigQuery, …
• Terraform, Prometheus and Grafana.

Do you have experience in Terraform?, A senior, generalist, business-focused profile. Someone who picks the right tool to solve the actual business problem - not the shiniest one. Also:

• Accountable for your work.
• You thrive when given autonomy.
• Experience designing and building highly scalable and resilient distributed systems.
• Good understanding and experience working on the cloud.
• You write clean code. Quality is a first citizen, so you write tests at any level of the test pyramid.
• Solid backend skills, but not afraid to help on any other area. You actually enjoy going out of your comfort zone.
• A pragmatic problem solver.
• Solid experience with SQL and Data warehouses.
• Experience with async communication: Pub/Sub, Kafka, …
• You're already building with AI, not just talking about it. You have opinions on how it changes the craft.
• Willing to learn new stuff every day and share your knowledge with your colleagues.

Nice to have:

• BigData, ML and data engineering.
• Experience shipping SaaS / multi-tenant products.

• No bullshit politics.
• Truly remote-friendly and async culture.
• ️ Horizontal structures where transparency and speak-up aren't buzzwords, they're how we work.
• Ownership: we base our relationship on trust, we give our teams autonomy and a purpose to deliver value to the business. We're all part of the product team.
• We're realistic: we find challenges, face them, solve them creatively, and learn from our mistakes.
• The spin-off is starting now, so your impact will be huge.
• Rules are a good start, then break them.
• Insights-driven.
• DevOps culture: the faster we get feedback, the better.
• AI-native way of working: we use it to think, plan, communicate, code, and share context.
• ️ Healthy life balance., * 50-65K + bonus (10-15%).
• ️ 1K for training + online English lessons.
• 40% discount (companions included) on any hotel, apartment or hostel operated by Líbere.

Líbere, as part of ALL IRON GROUP, was created by the founders of Ticketbis (acquired by eBay in 2016). What started as a bet on the largest alternative to hotels in Europe has grown into something bigger: +1500 units under operation, 6 countries, doubling revenue every year, and hitting break-even this year. Our initial vision got validated along the way. We built a software platform to support a new modern operating model for hotels - and it works so well that we're now applying it to all our hotels and pivoting hard into this model because of how efficient it is at scale. So now we're going one step further: we're spinning off the product as SaaS so any hotel chain willing to ride this crazy wave of changes can adopt it in a fast and reliable way. Big challenge for the team. Huge opportunity for whoever joins. What we've built After 5 years operating hotels with this model, we've turned what we learned into a platform built on five principles - and each one is an interesting engineering problem: * Autonomy - guests check in, access their room, and manage their stay without waiting for anyone. Making that work means a system reliable enough that 96% of stays complete without any staff intervention. Compliance, validation, and edge cases all resolved before arrival day, not at the front desk. * ️ Automation as the default - not a layer on top of manual workflows. The system drives the flow; humans handle explicit exceptions from a queue. We don't monitor timelines, we resolve exceptions. This is the part that flipped our whole engineering model. * All-in-one - pricing, policies, access rules, communications, distribution… one decision surface, applied everywhere. No third-party handoffs limiting how deep automations can go, which means cross-domain automations (housekeeping distribution pricing access) run natively. Plenty of meaty problems here. * Chain-first architecture - most hospitality software was designed per-property and breaks at scale. Ours is built so configurations collapse into a small set of reusable definitions and inherit across the portfolio. Adding a property is cheap; the leverage compounds. * Zero-management - when the platform guarantees correctness, management becomes the exception, not the safety net. This isn't a slogan, it's a forcing function on every design decision we make. And here's where AI clicks in Our exception-driven approach toward zero-management turned out to be the perfect fit for the AI wave: automation AI agent HITL. We didn't pivot to "do AI" - AI just clicked into the architecture we already had. Most platforms bolt AI on top of manual workflows; ours was built for delegation from day one, so AI agents extend an already autonomous system instead of fighting it. And we changed the way we build around it - not only how we code, but how we plan our work, communicate, and share knowledge. AI is also validating something we always believed: product engineers are valuable for their knowledge, context, big-picture thinking, and problem-solving mentality. Seniority on these soft skills matters more than ever, not less.