Forward Deployed Engineer (m/f/d)

Blueocean Technologies Gmbh · Berlinjunior

En corto

▸Trabajas directamente en empresas de oficios, observando el trabajo real para construir agentes de IA que resuelven problemas cotidianos.
▸Desarrollas desde cero soluciones en múltiples tecnologías, con responsabilidad real sobre agentes en producción que afectan ingresos.
▸El rol exige estar cerca del cliente, tomar decisiones rápidas y medir impacto en tiempo real, no en especulaciones.

No se requiere inglés, pero el candidato debe estar dispuesto a comunicarse con equipos in

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¿Qué piden?

✓Experiencia en desarrollo end-to-end de productos, desde arquitectura hasta entrega y mantenimiento.
✓Capacidad para tomar decisiones sobre qué construir sin especificaciones formales.
✓Habilidad para hablar con clientes reales y cambiar de opinión basándose en sus feedbacks.
✓Capacidad de iterar rápidamente, construyendo y desplegando múltiples veces al día.
✓Curiosidad profunda por problemas reales, más que por tecnologías específicas.
✓Capacidad de mantener el equilibrio entre lanzar rápido y garantizar durabilidad a largo plazo.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

PythonFastAPIasync SQLAlchemyPostgreSQLpgvectorCeleryRedisVue 3TypeScriptVite

¿A quién escribirle en Blueocean Technologies Gmbh?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

⭐️ Your Impact: The European trades are one of the least digitised industries left. Software penetration sits under 15%, against roughly 70% in the US. The labour productivity gap runs about 30%. Millions of skilled people spend their evenings on paperwork instead of the craft they trained for — in the industry that has to deliver the energy transition. There is almost no incumbent software to displace. That is unusual, and it won't last. smalt replaces the back office entirely rather than selling Meister another tool to manage. In the last six months that went from a partner app and a dashboard to around thirty AI agents in production - pricing real jobs, qualifying real leads, running the operations of businesses whose payroll depends on it working. These days building thirty agents is easy. Knowing which thirty is what's challenging. That only comes from being in the Betrieb and talking to the Handwerker. That's what this role is for. What you'll do You'll sit in Handwerksbetrieben - at the Meister's desk, in the van, on site, next to our team - and watch how the work actually happens. Then you'll come back and build the thing that fixes it, often multiple times on the same day. - Spend real time with partners. Not a quarterly customer call. You'll know our Meister by name, understand their P&L, and notice the thing they've stopped complaining about because they assume it can't be fixed. - Build across the stack. Python/FastAPI services, Vue interfaces, Flutter screens, agent loops, data pipelines - whatever the problem needs. - Own agents in production. Not demos. Agents that price real jobs, answer real customers, and cost real money when they're wrong. Reliability, evaluation, structured output, graceful failure. - Decide what to build. You'll write your own acceptance criteria. Nobody here will hand you a spec, and waiting for one is how to fail in this role. - Measure whether it worked. Hours saved per partner, offers that go out untouched, leads answered before a competitor picks up. If the number didn't move, it didn't work. What that looks like in practice In July one of our Meister got an early build of the partner app, ahead of the general rollout. He tested it between jobs and sent screenshots: from a calendar appointment he could no longer jump into the project to pull the customer's phone number. He had a reply in two minutes. Within the hour he'd also asked for a navigation button - tap the address, go straight to maps. Neither was news. Both were already being worked on before he hit send. We aim to be fast, and close enough to the work that we've usually seen the problem before the person living it has to tell us. ✨ What Makes You a Great Fit: You might be a great fit if you - Have owned something end to end - architecture through delivery through the unglamorous iteration afterwards. We don't count years; we look at what you carried. - Get obsessed with a problem rather than a stack. The tools change every few months. The curiosity compounds. - Would rather ship something that changes a tradesperson's week than win an argument about abstractions. - Actually like talking to customers, and have changed your mind about a feature because of something a user said. - Are comfortable being the least knowledgeable person in a room full of electricians, and ask the question anyway. - Can hold "ship it today" and "this needs to survive two years" in your head at the same time, and know which one applies. Our stack, so you know what you're walking into: - Backend: Python, FastAPI, async SQLAlchemy, PostgreSQL (with pgvector), Celery, Redis - Frontend: Vue 3, TypeScript, Vite, PrimeVue - Mobile: Flutter - AI: Anthropic, Open source and Google models, vector search over partner and catalog data - Infra: Google Cloud Run, Cloud SQL, Sentry We care that you're strong somewhere and unafraid everywhere else.

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