We're offering
- $250K OTE
- 3-4% equity in a notable VC-backed company approaching Seed
- $100K+ post-Seed salary uplift
- Full ownership of a category-defining physical AI architecture
Must be Austin TX based or willing to relocate.
We're seeking
We are building multimodal physical AI agents that operate directly on the factory floor-reasoning over video, sensors, PLCs, and enterprise systems to drive real-world decisions in manufacturing, logistics, and energy.
Most AI today is built for language. It cannot understand machines, processes, or physical operations. Meanwhile, massive amounts of industrial intelligence remain trapped in sensors and systems.
We are redesigning the AI architecture for the physical world-and we're seeking a hands-on VP of Engineering (effectively our CTO) to build it with us.
Team you will join
You'll join a small, highly technical team of builders with deep experience across industrial AI, robotics, and real-world systems. The team includes ex-Palantir engineers, a former ABB robotics VP, and autonomous systems engineers from Audi and Volvo, alongside researchers from Harvard and MIT.
What you will do
- Architect and build our physical AI system-from edge devices (cameras, vibration/thermal sensors, PLCs via OPC-UA/Modbus) to cloud-enabling agents to operate directly on real-world machinery and processes
- Design real-time systems that ingest and interpret raw signals (video streams, time-series sensor data, PLC states) to understand machine behavior, line states, and failure modes
- Build the ontology that grounds agents in physical operations—machines, sequences, constraints, and state transitions across production and logistics systems
- Develop agentic control loops for quality, maintenance, and operations-detecting deviations, reasoning over root cause, and triggering actions (alerts, work orders, schedule adjustments)
- Stay hands-on in core systems: video pipelines, edge inference, streaming data systems, and low-latency processing across distributed environments
- Lead and scale a small, high-performance team while remaining the primary technical driver of architecture and execution
- Design systems that improve with deployment-capturing machine behaviors, failure signatures, and operational patterns across sites