Embedder

Compensation

Full Description

As a Founding Engineer, you will architect the systems that allow LLMs to understand the physical world. You won't just be chaining API calls; you will build the multimodal ingestion pipelines that transform raw schematics into structured knowledge, design the secure context management systems that handle strictly confidential IP, and engineer the verification workflows that ensure code runs correctly on target hardware. Example Projects: High Precision RAG: Design ingestion engines capable of decomposing complex technical documents, extracting semantic meaning from layouts, block diagrams, and performance graphs to feed our knowledge base. Closed-Loop Verification: Architect the automated feedback mechanisms that validate agent-generated code, orchestrating static analysis, simulation, and Hardware-in-the-Loop (HIL) testing to ensure strict adherence to constraints. Secure Infrastructure: Build scalable, project-scoped environments that support flexible deployment options, from cloud-native VPCs to air-gapped on-premise installations for enterprise clients. Preferred Qualifications: Systems Fluency: You are comfortable working across the stack, from designing backend services to understanding the nuances of embedded toolchains and compilation processes. LLM/RAG Experience: You have built production RAG systems and understand the nuances of reranking, vector stores, and managing context for large-scale technical corpora. Hardware Curiosity: You don't need to be an electrical engineer, but you should be interested in how software interacts with hardware constraints like bus protocols, register maps, and clock domains. High Agency: You will own core platform components, from data ingestion to analytics pipelines, taking them from design to production deployment. Why Embedder: Solve a Hard, Real-World Problem: We aren't building another wrapper. We are automating the development workflow for safety-critical systems where accuracy is paramount. Deep Tech Stack: Our architecture requires solving novel problems in multimodal document understanding, knowledge graph construction, and secure automation for physical hardware. Founding Equity: As a core member of the early team, you will have significant ownership of both the product's technical direction and the company itself.