Full-Stack Engineer
Role details
Job location
Tech stack
Job description
from the first commit to production monitoring. We ship fast, identify what's imperfect, and build systems as friction emerges. 1. Ship Features Fast, Build Platform as You Go Design and ship end-to-end features (Next. Js front-end * Fast API back-end * Supabase) Identify when manual deploys/testing/monitoring hurt, automate them. Create reusable patterns for common integration needs (data-access, webhooks, auth, data sync) You'll ship the feature this week, automate the deployment next week, extract patterns the month after. 2. Integration Architecture for HR Tech Stack Design API patterns that work for ATS, HRIS, Linked In, email providers, and future integrations. Build webhook handlers, auth flows (OAuth, JWT), data sync pipelines. Make integrations testable, observable, and resilient from day one. Monitoring and self-healing is critical. Think about how to "eat " external providers when appropriate. 3. Safe Deployment & Monitoring Set up monitoring/tracing for
Requirements
every feature you ship (know what breaks and where) Create deployment automation as manual deployment pain increases. Build internal tooling to make deployments safe, routine, and low-friction. Know when to ask for help setting up observability, then automate it for next time Our stack: Python/Fast API, Next. Js 14+, Supabase, Docker, Git Hub Actions, and infrastructure as code patterns. You AreMust-haves: 4+ years professional software engineering (full-stack) Proven ability to ship features end-to-end (Next. Js + Python/Fast API preferred) Experience and excitement towards AI Agents (coding agents, LLM APIs) Experience with monorepos, deployment automation, CI/CD, Docker. Strong API, webhook, and authentication pattern knowledge (OAuth, JWT) Balance pragmatism and perfection - ship fast, know what's imperfect, fix systematically. AI/LLM proficiency is required**: You are a heavy user of AI coding agents (Claude, Cursor, Git Hub Copilot, or similar) and LLMs in your daily workflow. AI-assisted development is not optional - it will be expected and enforced. Ownership mindset: You own features from first commit to production monitoring. You automate when manual work becomes painful, not before. You ask for help setting up observability when needed, then automate it. You identify where things need monitoring and either set it up or elevate appropriately. We test for: Can you ship a feature AND identify where it needs monitoring? When you encounter friction (deploys, testing, integration), do you automate or accept it? Can you collaborate with founders on technical decisions while still moving fast? xhfqzwm Do you think in systems - how does this feature connect to everything else? Nice to Have: Prior experience at pre-Series A startups (", "employmentType": "FULL_TIME", "industry": "FULL STACK", "jobLocation" : { "@type": "Place", "address": { "@type": "PostalAddress", "streetAddress": "Les", "addressLocality": "Les", "addressRegion": "Lleida", "addressCountry": "ES", "postalCode": "n/a" } }, "salaryCurrency": "EUR", "title": "Ai-native full-stack engineer (react/python) - bcn hybrid", "hiringOrganization" : { "@type" : "Organization", "name" : "AI Firm" } }