AI Software Engineer (Applied AI)

Snapbau is building the AI operating system for construction.

Our platform manages the complete procurement and execution lifecycle of construction projects—from tenders and purchasing to deliveries, subcontractors, invoices, budgets and site coordination.

Today, several major construction companies use Snapbau to digitise and automate critical operational workflows across Switzerland, with expansion underway into France and other European markets.

Rather than building isolated AI features, we are embedding intelligence into every operational workflow, allowing construction companies to automate decisions, reduce administrative work, improve cost control and execute projects significantly more efficiently.

We're looking for engineers who want to build production AI systems that solve difficult real-world problems at scale.

The Role

1. You will become part of the team building Snapbau's AI platform.
2. Your work will focus on designing, building and deploying production-grade AI systems that automate complex construction workflows across procurement, project execution and financial operations.
3. This is a highly technical product engineering role with significant ownership.
4. You'll work directly on AI features that are used by construction companies every day—not research prototypes.

Tasks

Responsibilities

• Build production AI features used by construction companies daily.
• Design scalable AI architectures capable of handling millions of documents and complex, nested datasets.
• Integrate LLMs into reliable business workflows rather than standalone chat experiences.
• Develop APIs and services powering Snapbau's AI platform (FastAPI, Uvicorn).
• Develop and maintain robust core Python applications, seamlessly blending advanced AI workflows with traditional software engineering.
• Act with a high degree of autonomy while proactively engaging with business stakeholders to understand their needs and translate them into robust software applications.
• Write robust test suites (Pytest) to ensure data integrity across complex product resolution algorithms.
• Continuously improve model accuracy using real customer feedback.

Requirements

Required:

• Strong Python development skills (Pydantic, Pandas).
• Experience building and deploying REST APIs (ideally FastAPI).
• Experience integrating LLM APIs (specifically Google GenAI / Gemini, or OpenAI / Anthropic).
• Experience dealing with document parsing (PyMuPDF, OCR) and Excel data manipulation (Openpyxl, Pandas).
• Excellent database knowledge (SQL/MySQL, and NoSQL like Firestore).
• Strong understanding of software engineering best practices and writing robust unit tests.
• Comfortable working with large, messy datasets and edge cases.
• Strong problem-solving ability.
• Good knowledge of CI/CD with GitHub.

Preferred:

• Experience with LangGraph and agentic workflows.
• Familiarity with traditional Machine Learning techniques for specific product aspects.
• Experience with the GCP ecosystem (Cloud SQL, Google Cloud Storage).
• Streaming responses (Server-Sent Events / sse-starlette).
• RAG systems, Vector databases, and Embeddings.
• Docker and containerized microservices deployments.
• Construction industry experience is a bonus, but not required.

We're looking for engineers who:

• Enjoy solving difficult product problems.
• Care about building reliable production systems and rigorous testing.
• Are highly autonomous, yet comfortable taking ownership and communicating directly with domain experts.
• Are exceptional builders—whether your absolute strength is in cutting-edge agentic AI or pure Python backend engineering, we want to hear from you.
• Enjoy working in fast-moving startup environments.