Senior Backend & AI/RAG Engineer (GCP Specialist)

We are looking for a talented Senior Backend and AI Engineer to join us as our Founding Engineer to build a dynamic, real-time analysis platform. You won't just be writing code; you will take full ownership of shaping our technological foundation. Please note: As we are currently bootstrapping, this is an equity-only role designed for someone looking to be a key part of our founding team and build something massive from the ground up.

• Architectural Design: Design and implement a real-time RAG architecture utilizing Vertex AI (Gemini Flash) and Vector Databases.
• Backend Pipelines: Build efficient backend pipelines to process user-uploaded architectural files and inject them into LLM contexts dynamically.
• Real-Time Streaming: Implement real-time streaming responses (Server-Sent Events / WebSockets) from LLMs to the Web frontend to ensure sub-second perceived latency.
• Geospatial Integration: Manage geospatial data integration and mapping engines (handling CRS, EPSG, and spatial boundaries).
• Infrastructure Optimization: Optimize serverless infrastructure on GCP (Cloud Run, Cloud Functions) to handle concurrent live LLM sessions efficiently.

• 4+ years of experience in Backend development (Python heavily preferred due to AI/GIS ecosystem).
• Proven experience building Production-grade RAG systems and working with LLM APIs (Vertex AI / OpenAI).
• Strong experience with the GCP serverless stack: Cloud Run, Cloud Functions, Cloud Storage.
• Streaming Expertise: Experience with streaming APIs and handling JSON/Structured outputs from LLMs in real-time.
• Startup DNA: Highly driven, self-managed, and excited about the startup journey and an equity-focused compensation model.

• Experience parsing and extracting geometric/metadata from BIM/IFC files (e.g., using IfcOpenShell).
• Experience with Vector Databases (Pinecone, Chroma, or BigQuery Vector Search).
• Solid understanding of prompt optimization techniques (Context Caching, Few-shot routing).
• Familiarity with GIS/Geospatial concepts, spatial data libraries (Shapely, Pyproj, GeoPandas), or spatial queries in BigQuery.

Please feel free to contact @yaninkliro or @michalgrinvald for any deets.