About Infi Robotics
Infi’s mission is to unlock physical abundance and reindustrialize America by building the Universal Factory: a fully autonomous, general-purpose factory that can turn any design into a finished product.
We are a robotics-native contract manufacturer helping hardware companies scale from prototype to production at our factory in the San Francisco Bay Area. Our initial focus is automated assembly for robots, drones, and other intelligent hardware.
The role
Build the software backbone of a programmable factory: the systems customers use to get products built, the tools operators use on the floor, and the services that connect production. You will turn customer requirements into useful workflows, reliable records, and clear decisions, working directly with the people building the hardware. This is a broad software engineering role with ownership across product, architecture, and implementation.
What you'll do
Build the factory software connecting customer requirements, bills of materials, design revisions, assembly instructions, quality checks, and delivery records.
Create customer portals for project intake and build status, and operator tools for assembly, measurements, defects, and exception handling.
Connect workflows to robotic cells and equipment, with practical scheduling, traceability, task handoffs, and recovery when things fail.
Work directly with customers and operators to ship useful software, improve it through real builds, and decide what to build versus integrate.
What you'll bring
Experience shipping and maintaining software people depend on, with substantial ownership from problem definition through deployment.
Strong full-stack skills, including TypeScript or comparable frontend experience and backend development in Python, Go, Rust, or another suitable language.
Sound judgment about APIs, relational data models, testing, logging, permissions, and handling partial failures while keeping records correct.
Comfort turning ambiguous user needs into simple workflows. Manufacturing systems, hardware integrations, event-driven software, and ML data or evaluation tools are useful additional experience.