Forward Deployed Engineer

Description

Job Summary: We are seeking a Forward Deployed Engineer to lead high-impact projects, leveraging AI to revolutionize construction. Key Highlights: 1. Revolutionizing construction with AI and end-to-end solutions. 2. High-impact projects with autonomy from problem identification to launch. 3. A dynamic and ambitious environment focused on sustainability. At 011h, we are revolutionizing the construction industry to make it more sustainable, efficient, and digital. We design and build buildings with an industrialized vision, using innovative technologies and planet-friendly materials such as wood. Our mission is clear: to build better—for everyone. We are Europe's first digital "end-to-end" construction platform. We combine architectural and engineering expertise with the power of technology to standardize processes, automate tasks, and scale solutions that transform the industry—without compromising design, quality, or positive impact. At 011h, professionals from design, construction, and software collaborate in a dynamic, ambitious, and sustainability-oriented environment. If you're inspired by the idea of changing how the world is built, this is your place. Currently, our operations are focused on Spain, with plans for international expansion in the coming years. At 011h, we are looking for a Forward Deployed Engineer to join our team. **The Challenge** Most of our engineering work flows through product teams: a PM frames the problem, a Tech Lead decomposes it, and the team builds it. This model works well for our platform—but not for a class of high-impact work that lives at the intersection of engineering, construction domain expertise, and our operations: ambiguous, messy problems where the fastest path to value is an engineer sitting directly with the problem—not behind a backlog. The Forward Deployed Engineer owns this work, and AI is their primary tool: much of the solution you’ll build will be AI-native (agents, LLMs, end-to-end process extraction and automation), with AI acting as a multiplier at every step. Our CPO defines which major problems to tackle—the what—and the Head of Engineering frames how to attack them—the how. From there, the project is yours: you speak directly with the end user to understand the real pain point to solve, propose multiple solutions and decide on the best one, validate the approach by putting a prototype in their hands, then build and launch it. And you do it at high velocity: delivering roughly one project every \~3 weeks. **Requirements** **What You’ll Do at 011h?** * Work side-by-side with business teams (Project Management, Design, Operations, and Product) to understand, frame, and solve high-impact problems that still lack a clear specification. * Design and build end-to-end solutions—from data pipelines and OCR/extraction workflows to internal automations and AI-augmented tooling—taking them from prototype to production. * Stay hands-on from start to finish: speak with the domain expert, write the specification, and deliver the code—often without a PM intermediating. * Build AI-native by default: intensive use of Claude Code and our internal AI platform as a natural part of how you build. * Decide what’s worth building, buying, or leaving alone—and communicate that clearly. * Scale proven solutions toward their final scope: hand off mature work to a product team when appropriate, rather than accumulating an ownerless backlog. * Collaborate cross-functionally with Digital Product Management, Product Design, and the rest of Engineering—sharing learnings and elevating our AI-native culture. **Tech Stack** * Backend: Python with FastAPI, domain-driven microservice architecture (DDD), APIs-first. * Frontend: TypeScript with React, Zustand (global state management), TanStack, React Router. * Data & Messaging: PostgreSQL, RabbitMQ (with Protocol Buffers for message serialization), Redis. * Infrastructure & Deployment: AWS, EKS, ArgoCD, Helm, Terraform, KEDA, GitLab CI, Docker. * Quality: Automated testing (Jest, React Testing Library, Cypress, Pytest), Security by Design. * AI & Productivity: Claude Code, CodeRabbit, n8n, MCPs from our tools and other tools we’ll integrate as part of our AI-native strategy. **Who Are We Looking For?** * 5+ years of software development experience building and shipping production products. * Demonstrable experience automating business workflows and processes with AI: agent/LLM orchestration, system integrations, and end-to-end pipelines that reduce manual effort. * Senior generalist profile: comfortable across the stack (backend, data, and frontend when needed), optimizing for value delivery over specialization in a single layer. * Strong experience with Python/FastAPI and fluency with TypeScript/React (or vice versa), with willingness to move fluidly across both sides. * Proven track record of autonomously delivering end-to-end solutions: from understanding an ambiguous problem to designing, building, and deploying it into production. * Product mindset: you think in terms of outcomes and trade-offs, operate effectively without a PM intermediary, and know when to involve one. * Domain curiosity: you’re genuinely interested in how construction, procurement, and operations truly work—and ask questions until you understand the problem better than the person who brought it to you. * Experience with AI-assisted development workflows (Claude Code, Cursor, Copilot, or similar) and sound judgment about where they add value—and where they don’t. * Ability to collaborate cross-functionally with Product, Design, and other teams, and to communicate technical trade-offs to non-technical audiences. * Fluent communication in both Spanish and English. **Benefits** * Prior experience as a forward-deployed engineer, solutions engineer, growth engineer, applied engineer, founding engineer, or in roles combining hands-on engineering with product responsibility. * Prior experience in construction tech, PropTech, AEC, or BIM/IFC tools. * Experience with automation and orchestration tools (n8n, Make/Zapier, or similar) and with building agent-based workflows in production. * Experience building or integrating AI pipelines into products (LLMs, OCR, agents, RAG, evals). * Experience with relational databases (PostgreSQL) and event-driven architectures (RabbitMQ, Kafka, or other brokers).