# Founding Full-Stack Engineer - Company: [Dryft]() - Location: San Francisco - Team: Engineering - Employment type: Full Time - Posted: August 7, 2025 ## Job description ## DRYFT **Dryft builds intelligent systems that automate complex human decisions in manufacturing operations** We’re a small, talent-dense team with modest roots and a love for the physical world - cars, machines, planes. Our team includes graduates from **Stanford, Berkeley, CDTM, TUM**, winners of **Stanford TreeHacks**, recipients of **Fulbright & Haniel scholarships**, and builders of everything from **robots and race cars to software with millions of downloads**. We’re backed by the founders and leaders behind Amazon, Facebook, Stripe, Applied Intuition, & others; General Catalyst & Neo, and board members of global industrial companies. Today, we’re already saving customers millions. But this is only the beginning. ERPs ran the physical world for half a century. Dryft is powering the next. ## **THE ROLE** As **Founding Fullstack Engineer**, you’ll be the brain behind Dryft’s decision intelligence. You’ll build scalable systems that combine agent-based reasoning with mathematical optimization and simulation on top of large-scale industrial data. ## **YOU** * Like building **scalable, interpretable, data-driven agents** from all perspectives - algorithms, architecture and infrastructure. * Have a **strong product sense** and enjoy working directly with customers daily * Have **shipped production code end-to-end,** are strong in backend & infra and comfortable shipping basic frontend features. * Have built **data-intensive**, **multi-tenant production systems** with Redis, Postgres, and orchestration frameworks. Clickhouse experience is a plus. * Are ready to work **onsite in SF** (we support relocation & visa) ## **TECH STACK** * **FE (TypeScript):** React, Chakra UI v3, TanStack Router, TanStack Query, Vite * **BE (Python):** FastAPI with Pydantic v2, SQLModel, Postgres with pgvector, dagster * **AI:** Pydantic AI, Langfuse ## Apply [Apply on Dryft]() Canonical job page: