Build and scale our capture-to-cloud pipeline (ingestion, uploads, processing, storage, access)
Drive performance work across compression, reliability, observability, and robustness of our data pipeline.
Build internal services and tools that unblock capture and operations teams
Partner closely with ops to shorten the loop from capture to customer-ready data
Help define technical direction and engineering best practices as the team scales

Strong backend fundamentals: distributed systems, APIs, databases, queues, storage
Experience owning systems end to end, including when things break
Comfort operating without a lot of structure and helping create it
Product-minded builder who is comfortable translating real world feedback into better systems and experiences
Clear communicator with high accountability
Emotional maturity and good judgment under pressure
Bonus points: Robotics, autonomy, CV, or sensor-adjacent environments
Bonus points: Video pipelines, media processing, or large-file transfer experience
Bonus points: Internal tooling or ops-support systems

A world-changing problem: Physical AI will reshape entire industries, but it cannot scale without real-world data. Trace is addressing one of the core constraints holding the field back.
Early but real traction: Active pilots with growing demand on both sides of the marketplace.
Experienced, tight-knit team: Ex founders, PhDs, and operators with a track record of building and scaling together.
Real ownership: This is early. Your work will materially shape the product, systems, and direction of the company.
Foundational platform: We are building core infrastructure that enables many future products and use cases as physical AI evolves.

Software Engineer, Backend – Data Systems, AI/Robotics

Key skills