Founding Engineer - Data

The Role: You'll be the person who turns a company's fragmented information into a company brain that AI agents can trust. You'll design and build the backend systems that ingest, organize, connect, and retrieve decades of enterprise knowledge. The hard part goes well beyond moving data from one place to another. A property might have different names across systems. Documents can contradict one another. Important context can sit in a spreadsheet, a drawing, or an email thread. You'll figure out how to preserve those relationships and give an agent the right information for the task in front of it. This role combines backend engineering, data architecture, and experimentation. You'll work closely with our CTO and the Infrastructure and Deployment engineers. You'll own production pipelines and processing infrastructure, with particular depth in data modeling, reconciliation, retrieval, and context quality. What you'll build Ingestion and processing pipelines across databases, PDFs, policies, drawings, spreadsheets, and emails Backend services and shared data infrastructure that turn customer integrations into reusable capabilities Data models and entity relationships that connect information across fragmented systems Parsing, extraction, deduplication, and reconciliation methods that work on messy real-world data Storage, indexing, and retrieval systems that give agents relevant context while preserving sources and access permissions Evaluation and observability that make extraction quality, freshness, retrieval accuracy, latency, and cost measurable Processing architectures designed to grow to billions of rows and large document collections, with reliable updates and reprocessing Tech stack and tools

Relevant experience includes: Languages and backend: Python, TypeScript, Node.js, SQLData platforms and pipelines: PostgreSQL, Snowflake, Databricks, Amazon Redshift, dbtAI and agents: Anthropic and OpenAI APIs, Claude Agent SDK, Vercel AI SDK, LangGraph, MCPRetrieval and memory: pgvector, Cohere, Hindsight, RAG pipelines Workflows and compute: Inngest, Temporal, Blaxel, ModalCloud and infrastructure: AWS, Docker, Kubernetes, Terraform We value experience building production systems with these or comparable technologies.